Publications

2023

2022

198. Frustration-driven allosteric regulation and signal transmission in the SARS-CoV-2 spike omicron trimer structures: a crosstalk of the omicron mutation sites allosterically regulates tradeoffs of protein stability and conformational adaptability.
     Verkhivker G, Agajanian S, Kassab R, Krishnan K. Physical Chemistry Chemical Physics. 2022. 24(29), 17723-17743. doi: 10.1039/D2CP01893D.

     Abstract

     Dissecting the regulatory principles underlying function and activity of the SARS-CoV-2 spike protein at the atomic level is of paramount importance for understanding the mechanisms of virus transmissibility and immune escape. In this work, we introduce a hierarchical computational approach for atomistic modeling of allosteric mechanisms in the SARS-CoV-2 Omicron spike proteins and present evidence of a frustration-based allostery as an important energetic driver of the conformational changes and spike activation. By examining conformational landscapes and the residue interaction networks in the SARS-CoV-2 Omicron spike protein structures, we have shown that the Omicron mutational sites are dynamically coupled and form a central engine of the allosterically regulated spike machinery that regulates the balance and tradeoffs between conformational plasticity, protein stability, and functional adaptability. We have found that the Omicron mutational sites at the inter-protomer regions form regulatory hotspot clusters that control functional transitions between the closed and open states. Through perturbation-based modeling of allosteric interaction networks and diffusion analysis of communications in the closed and open spike states, we have quantified the allosterically regulated activation mechanism and uncover specific regulatory roles of the Omicron mutations. Atomistic reconstruction of allosteric communication pathways and kinetic modeling using Markov transient analysis reveal that the Omicron mutations form the inter-protomer electrostatic bridges that operate as a network of coupled regulatory switches that could control global conformational changes and signal transmission in the spike protein. The results of this study have revealed distinct and yet complementary roles of the Omicron mutation sites as a network of hotspots that enable allosteric modulation of structural stability and conformational changes which are central for spike activation and virus transmissibility.

      
199. Probing Mechanisms of Binding and Allostery in the SARS-CoV-2 Spike Omicron Variant Complexes with the Host Receptor: Revealing Functional Roles of the Binding Hotspots in Mediating Epistatic Effects and Communication with Allosteric Pockets.
     Verkhivker G, Agajanian S, Kassab R, Krishnan K. Int J Mol Sci. 2022. 23(19):11542. doi: 10.3390/ijms231911542. PMID: 36232845.
     Abstract

     In this study, we performed all-atom MD simulations of RBD-ACE2 complexes for BA.1, BA.1.1, BA.2, and BA.3 Omicron subvariants, conducted a systematic mutational scanning of the RBD-ACE2 binding interfaces and analysis of electrostatic effects. The binding free energy computations of the Omicron RBD-ACE2 complexes and comprehensive examination of the electrostatic interactions quantify the driving forces of binding and provide new insights into energetic mechanisms underlying evolutionary differences between Omicron variants. A systematic mutational scanning of the RBD residues determines the protein stability centers and binding energy hotpots in the Omicron RBD-ACE2 complexes. By employing the ensemble-based global network analysis, we propose a community-based topological model of the Omicron RBD interactions that characterized functional roles of the Omicron mutational sites in mediating non-additive epistatic effects of mutations. Our findings suggest that non-additive contributions to the binding affinity may be mediated by R493, Y498, and Y501 sites and are greater for the Omicron BA.1.1 and BA.2 complexes that display the strongest ACE2 binding affinity among the Omicron subvariants. A network-centric adaptation model of the reversed allosteric communication is unveiled in this study, which established a robust connection between allosteric network hotspots and potential allosteric binding pockets. Using this approach, we demonstrated that mediating centers of long-range interactions could anchor the experimentally validated allosteric binding pockets. Through an array of complementary approaches and proposed models, this comprehensive and multi-faceted computational study revealed and quantified multiple functional roles of the key Omicron mutational site R493, R498, and Y501 acting as binding energy hotspots, drivers of electrostatic interactions as well as mediators of epistatic effects and long-range communications with the allosteric pockets.
200. Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration.
     Krishnan K, Kassab R, Agajanian S, Verkhivker G. Int J Mol Sci. 2022. 23(19):11262. doi: 10.3390/ijms231911262. PMID: 36232566.

     Abstract

     In the current study, we introduce an integrative machine learning strategy for the autonomous molecular design of protein kinase inhibitors using variational autoencoders and a novel cluster-based perturbation approach for exploration of the chemical latent space. The proposed strategy combines autoencoder-based embedding of small molecules with a cluster-based perturbation approach for efficient navigation of the latent space and a feature-based kinase inhibition likelihood classifier that guides optimization of the molecular properties and targeted molecular design. In the proposed generative approach, molecules sharing similar structures tend to cluster in the latent space, and interpolating between two molecules in the latent space enables smooth changes in the molecular structures and properties. The results demonstrated that the proposed strategy can efficiently explore the latent space of small molecules and kinase inhibitors along interpretable directions to guide the generation of novel family-specific kinase molecules that display a significant scaffold diversity and optimal biochemical properties. Through assessment of the latent-based and chemical feature-based binary and multiclass classifiers, we developed a robust probabilistic evaluator of kinase inhibition likelihood that is specifically tailored to guide the molecular design of novel SRC kinase molecules. The generated molecules originating from LCK and ABL1 kinase inhibitors yielded ~40% of novel and valid SRC kinase compounds with high kinase inhibition likelihood probability values (p > 0.75) and high similarity (Tanimoto coefficient > 0.6) to the known SRC inhibitors. By combining the molecular perturbation design with the kinase inhibition likelihood analysis and similarity assessments, we showed that the proposed molecular design strategy can produce novel valid molecules and transform known inhibitors of different kinase families into potential chemical probes of the SRC kinase with excellent physicochemical profiles and high similarity to the known SRC kinase drugs. The results of our study suggest that task-specific manipulation of a biased latent space may be an important direction for more effective task-oriented and target-specific autonomous chemical design models.
201. Integrating Conformational Dynamics and Perturbation-Based Network Modeling for Mutational Profiling of Binding and Allostery in the SARS-CoV-2 Spike Variant Complexes with Antibodies: Balancing Local and Global Determinants of Mutational Escape Mechanisms.
     Verkhivker G, Agajanian S, Kassab R, Krishnan K. Biomolecules. 2022. 12(7):964. doi: 10.3390/biom12070964. PMID: 35883520.

     Abstract

     In this study, we combined all-atom MD simulations, the ensemble-based mutational scanning of protein stability and binding, and perturbation-based network profiling of allosteric interactions in the SARS-CoV-2 spike complexes with a panel of cross-reactive and ultra-potent single antibodies (B1-182.1 and A23-58.1) as well as antibody combinations (A19-61.1/B1-182.1 and A19-46.1/B1-182.1). Using this approach, we quantify the local and global effects of mutations in the complexes, identify protein stability centers, characterize binding energy hotspots, and predict the allosteric control points of long-range interactions and communications. Conformational dynamics and distance fluctuation analysis revealed the antibody-specific signatures of protein stability and flexibility of the spike complexes that can affect the pattern of mutational escape. A network-based perturbation approach for mutational profiling of allosteric residue potentials revealed how antibody binding can modulate allosteric interactions and identified allosteric control points that can form vulnerable sites for mutational escape. The results show that the protein stability and binding energetics of the SARS-CoV-2 spike complexes with the panel of ultrapotent antibodies are tolerant to the effect of Omicron mutations, which may be related to their neutralization efficiency. By employing an integrated analysis of conformational dynamics, binding energetics, and allosteric interactions, we found that the antibodies that neutralize the Omicron spike variant mediate the dominant binding energy hotpots in the conserved stability centers and allosteric control points in which mutations may be restricted by the requirements of the protein folding stability and binding to the host receptor. This study suggested a mechanism in which the patterns of escape mutants for the ultrapotent antibodies may not be solely determined by the binding interaction changes but are associated with the balance and tradeoffs of multiple local and global factors, including protein stability, binding affinity, and long-range interactions.

202. Conformational Dynamics and Mechanisms of Client Protein Integration into the Hsp90 Chaperone Controlled by Allosteric Interactions of Regulatory Switches: Perturbation-Based Network Approach for Mutational Profiling of the Hsp90 Binding and Allostery.
     Verkhivker GM. J Phys Chem B. 2022. doi: 10.1021/acs.jpcb.2c03464. PMID: 35853093.

     Abstract

     Understanding the allosteric mechanisms of the Hsp90 chaperone interactions with cochaperones and client protein clientele is fundamental to dissect activation and regulation of many proteins. In this work, atomistic simulations are combined with perturbation-based approaches and dynamic network modeling for a comparative mutational profiling of the Hsp90 binding and allosteric interaction networks in the three Hsp90 maturation complexes with FKBP51 and P23 cochaperones and the glucocorticoid receptor (GR) client. The conformational dynamics signatures of the Hsp90 complexes and dynamics fluctuation analysis revealed how the intrinsic plasticity of the Hsp90 dimer can be modulated by cochaperones and client proteins to stabilize the closed dimer state required at the maturation stage of the ATPase cycle. In silico deep mutational scanning of the protein residues characterized the hot spots of protein stability and binding affinity in the Hsp90 complexes, showing that binding hot spots may often coincide with the regulatory centers that modulate dynamic allostery in the Hsp90 dimer. We introduce a perturbation-based network approach for mutational scanning of allosteric residue potentials and characterize allosteric switch clusters that control mechanism of cochaperone-dependent client recognition and remodeling by the Hsp90 chaperone. The results revealed a conserved network of allosteric switches in the Hsp90 complexes that allow cochaperones and GR protein to become integrated into the Hsp90 system by anchoring to the conformational switch points in the functional Hsp90 regions. This study suggests that the Hsp90 binding and allostery may operate under a regulatory mechanism in which activation or repression of the Hsp90 activity can be pre-encoded in the allosterically regulated Hsp90 dimer motions. By binding directly to the conformational switch centers on the Hsp90, cochaperones and interacting proteins can efficiently modulate the allosteric interactions and long-range communications required for client remodeling and activation.

203. Frustration-driven allosteric regulation and signal transmission in the SARS-CoV-2 spike omicron trimer structures: a crosstalk of the omicron mutation sites allosterically regulates tradeoffs of protein stability and conformational adaptability.
     Verkhivker GM, Agajanian S, Kassab R, Krishnan K. Phys Chem Chem Phys. 2022 Jul 27;24(29):17723-17743. doi: 10.1039/d2cp01893d. PMID: 35839100.
     Abstract

     Dissecting the regulatory principles underlying function and activity of the SARS-CoV-2 spike protein at the atomic level is of paramount importance for understanding the mechanisms of virus transmissibility and immune escape. In this work, we introduce a hierarchical computational approach for atomistic modeling of allosteric mechanisms in the SARS-CoV-2 Omicron spike proteins and present evidence of a frustration-based allostery as an important energetic driver of the conformational changes and spike activation. By examining conformational landscapes and the residue interaction networks in the SARS-CoV-2 Omicron spike protein structures, we have shown that the Omicron mutational sites are dynamically coupled and form a central engine of the allosterically regulated spike machinery that regulates the balance and tradeoffs between conformational plasticity, protein stability, and functional adaptability. We have found that the Omicron mutational sites at the inter-protomer regions form regulatory hotspot clusters that control functional transitions between the closed and open states. Through perturbation-based modeling of allosteric interaction networks and diffusion analysis of communications in the closed and open spike states, we have quantified the allosterically regulated activation mechanism and uncover specific regulatory roles of the Omicron mutations. Atomistic reconstruction of allosteric communication pathways and kinetic modeling using Markov transient analysis reveal that the Omicron mutations form the inter-protomer electrostatic bridges that operate as a network of coupled regulatory switches that could control global conformational changes and signal transmission in the spike protein. The results of this study have revealed distinct and yet complementary roles of the Omicron mutation sites as a network of hotspots that enable allosteric modulation of structural stability and conformational changes which are central for spike activation and virus transmissibility.

204. Biophysical Insight into the SARS-CoV2 Spike–ACE2 Interaction and Its Modulation by Hepcidin through a Multifaceted Computational Approach.
     Hadi-Alijanvand H, Di Paola L, Hu G, Leitner D, Verkhivker G, Sun P, Poudel H, Giuliani A. ACS Omega. 2022. doi: 10.1021/acsomega.2c00154.

     Abstract

     At the center of the SARS-CoV2 infection, the spike protein and its interaction with the human receptor ACE2 play a central role in the molecular machinery of SARS-CoV2 infection of human cells. Vaccine therapies are a valuable barrier to the worst effects of the virus and to its diffusion, but the need of purposed drugs is emerging as a core target of the fight against COVID19. In this respect, the repurposing of drugs has already led to discovery of drugs thought to reduce the effects of the cytokine storm, but still a drug targeting the spike protein, in the infection stage, is missing. In this work, we present a multifaceted computational approach strongly grounded on a biophysical modeling of biological systems, so to disclose the interaction of the SARS-CoV2 spike protein with ACE2 with a special focus to an allosteric regulation of the spike–ACE2 interaction. Our approach includes the following methodologies: Protein Contact Networks and Network Clustering, Targeted Molecular Dynamics, Elastic Network Modeling, Perturbation Response Scanning, and a computational analysis of energy flow and SEPAS as a protein-softness and monomer-based affinity predictor. We applied this approach to free (closed and open) states of spike protein and spike–ACE2 complexes. Eventually, we analyzed the interactions of free and bound forms of spike with hepcidin (HPC), the major hormone in iron regulation, recently addressed as a central player in the COVID19 pathogenesis, with a special emphasis to the most severe outcomes. Our results demonstrate that, compared with closed and open states, the spike protein in the ACE2-bound state shows higher allosteric potential. The correspondence between hinge sites and the Allosteric Modulation Region (AMR) in the S-ACE complex suggests a molecular basis for hepcidin involvement in COVID19 pathogenesis. We verify the importance of AMR in different states of spike and then study its interactions with HPC and the consequence of the HPC-AMR interaction on spike dynamics and its affinity for ACE2. We propose two complementary mechanisms for HPC effects on spike of SARS-CoV-2; (a) HPC acts as a competitive inhibitor when spike is in a preinfection state (open and with no ACE2), (b) the HPC-AMR interaction pushes the spike structure into the safer closed state. These findings need clear molecular in vivo verification beside clinical observations.

205. Hierarchical Computational Modeling and Dynamic Network Analysis of Allosteric Regulation in the SARS-CoV-2 Spike Omicron Trimer Structures: Omicron Mutations Cooperate to Allosterically Control Balance of Protein Stability and Conformational Adaptability
     Verkhivker G, Agajanian S, Kassab R, Krishnan K. Biorxiv. 2022. doi: https://doi.org/10.1101/2022.04.11.487920.
     Abstract

     Structural and computational studies of the Omicron spike protein in various functional states and complexes provided important insights into molecular mechanisms underlying binding, high transmissibility, and escaping immune defense. However, the regulatory roles and functional coordination of the Omicron mutations are poorly understood and often ignored in the proposed mechanisms. In this work, we explored the hypothesis that the SARS-CoV-2 spike protein can function as a robust allosterically regulated machinery in which Omicron mutational sites are dynamically coupled and form a central engine of the allosteric network that regulates the balance between conformational plasticity, protein stability, and functional adaptability. In this study, we employed coarse-grained dynamics simulations of multiple full-length SARS-CoV-2 spike Omicron trimers structures in the closed and open states with the local energetic frustration analysis and collective dynamics mapping to understand the determinants and key hotspots driving the balance of protein stability and conformational adaptability. We have found that the Omicron mutational sites at the inter-protomer regions form regulatory clusters that control functional transitions between the closed and open states. Through perturbation-based modeling of allosteric interaction networks and diffusion analysis of communications in the closed and open spike states, we quantify the allosterically regulated activation mechanism and uncover specific regulatory roles of the Omicron mutations. The network modeling demonstrated that Omicron mutations form the inter-protomer electrostatic bridges that connect local stable communities and function as allosteric switches of signal transmission. The results of this study are consistent with the experiments, revealing distinct and yet complementary role of the Omicron mutational sites as a network of hotspots that enable allosteric modulation of structural stability and conformational changes which are central for spike activation and virus transmissibility.
206. Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614G Mutant: Conformational Plasticity and Frustration-Induced Allostery as Energetic Drivers of Highly Transmissible Spike Variants.
     Verkhivker GM, Agajanian S, Kassab R, Krishnan K. J Chem Inf Model. 2022, 62, 8, 1956-1978. doi: 10.1021/acs.jcim.2c00124.
     Abstract

     The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern (VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model that can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising the folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the interprotomer hinge modulate the interdomain interactions, global mobility change, and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the interprotomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.
207. Computer Simulations and Network-Based Profiling of Binding and Allosteric Interactions of SARS-CoV-2 Spike Variant Complexes and the Host Receptor: Dissecting the Mechanistic Effects of the Delta and Omicron Mutations.
     Verkhivker GM, Agajanian S, Kassab R, Krishnan K. Int J Mol Sci. 2022, 23, 8, 4376. doi: 10.3390/ijms23084376.
     Abstract

     In this study, we combine all-atom MD simulations and comprehensive mutational scanning of S-RBD complexes with the angiotensin-converting enzyme 2 (ACE2) host receptor in the native form as well as the S-RBD Delta and Omicron variants to (a) examine the differences in the dynamic signatures of the S-RBD complexes and (b) identify the critical binding hotspots and sensitivity of the mutational positions. We also examined the differences in allosteric interactions and communications in the S-RBD complexes for the Delta and Omicron variants. Through the perturbation-based scanning of the allosteric propensities of the SARS-CoV-2 S-RBD residues and dynamics-based network centrality and community analyses, we characterize the global mediating centers in the complexes and the nature of local stabilizing communities. We show that a constellation of mutational sites (G496S, Q498R, N501Y and Y505H) correspond to key binding energy hotspots and also contribute decisively to the key interfacial communities that mediate allosteric communications between S-RBD and ACE2. These Omicron mutations are responsible for both favorable local binding interactions and long-range allosteric interactions, providing key functional centers that mediate the high transmissibility of the virus. At the same time, our results show that other mutational sites could provide a “flexible shield” surrounding the stable community network, thereby allowing the Omicron virus to modulate immune evasion at different epitopes, while protecting the integrity of binding and allosteric interactions in the RBD–ACE2 complexes. This study suggests that the SARS-CoV-2 S protein may exploit the plasticity of the RBD to generate escape mutants, while engaging a small group of functional hotspots to mediate efficient local binding interactions and long-range allosteric communications with ACE2.
208. Dissecting mutational allosteric effects in alkaline phosphatases associated with different Hypophosphatasia phenotypes: An integrative computational investigation.
     Xiao F, Zhou Z, Song X, Gan M, Long J, Verkhivker G, Hu G. PLoS Comput Biol. 2022,18, 3, e1010009. doi: 10.1371/journal.pcbi.1010009.
     Abstract

     Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control, mild and severe HPP phenotypes. Molecular dynamics simulations coupled with protein structure network analysis were employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and the developed machine learning model suggested that the topological network parameters could serve as a robust indicator of severe mutations. The results indicated that the severity of disease-associated mutations is often linked with mutation-induced modulation of allosteric communications in the protein. This study suggested that ALPL mutations associated with mild and more severe HPPs can exert markedly distinct effects on the protein stability and long-range network communications. By linking the disease phenotypes with dynamic and allosteric molecular signatures, the proposed integrative computational approach enabled to characterize and quantify the allosteric effects of ALPL mutations and role of allostery in the pathogenesis of HPPs.
209. Structural and Computational Studies of the SARS-CoV-2 Spike Protein Binding Mechanisms with Nanobodies: From Structure and Dynamics to Avidity-Driven Nanobody Engineering.
     Verkhivker G. Int J Mol Sci. 2022, 23, 6, 2928. doi: 10.3390/ijms23062928.
     Abstract

     Nanobodies provide important advantages over traditional antibodies, including their smaller size and robust biochemical properties such as high thermal stability, high solubility, and the ability to be bioengineered into novel multivalent, multi-specific, and high-affinity molecules, making them a class of emerging powerful therapies against SARS-CoV-2. Recent research efforts on the design, protein engineering, and structure-functional characterization of nanobodies and their binding with SARS-CoV-2 S proteins reflected a growing realization that nanobody combinations can exploit distinct binding epitopes and leverage the intrinsic plasticity of the conformational landscape for the SARS-CoV-2 S protein to produce efficient neutralizing and mutation resistant characteristics. Structural and computational studies have also been instrumental in quantifying the structure, dynamics, and energetics of the SARS-CoV-2 spike protein binding with nanobodies. In this review, a comprehensive analysis of the current structural, biophysical, and computational biology investigations of SARS-CoV-2 S proteins and their complexes with distinct classes of nanobodies targeting different binding sites is presented. The analysis of computational studies is supplemented by an in-depth examination of mutational scanning simulations and identification of binding energy hotspots for distinct nanobody classes. The review is focused on the analysis of mechanisms underlying synergistic binding of multivalent nanobodies that can be superior to single nanobodies and conventional nanobody cocktails in combating escape mutations by effectively leveraging binding avidity and allosteric cooperativity. We discuss how structural insights and protein engineering approaches together with computational biology tools can aid in the rational design of synergistic combinations that exhibit superior binding and neutralization characteristics owing to avidity-mediated mechanisms.
210. Exploring Mechanisms of Allosteric Regulation and Communication Switching in the Multiprotein Regulatory Complexes of the Hsp90 Chaperone with Cochaperones and Client Proteins: Atomistic Insights from Integrative Biophysical Modeling and Network Analysis of Conformational Landscapes.
     Verkhivker G. J Mol Biol. 2022, 167506. doi: 10.1016/j.jmb.2022.167506.
     Abstract

     Understanding molecular principles underlying Hsp90 chaperone functions and modulation of client activity is fundamental to dissect activation mechanisms of many proteins. In this work, we performed a computational investigation of the Hsp90-Hsp70-Hop-CR client complex to examine allosteric regulatory mechanisms underlying dynamic chaperone interactions and principles of chaperone-dependent client recognition and remodeling. Conformational dynamics analysis using high-resolution coarse-grained simulations and ensemble-based local frustration analysis suggest that the Hsp90 chaperone could recognize and recruit the GR client by invoking reciprocal dynamic exchanges near the intermolecular interfaces with the client. Using mutational scanning of the intermolecular residues in the Hsp90-Hsp70-Hop-GR complex, we identified binding energy hotspots in the regulatory complex. Perturbation-based network analysis and dynamic fluctuations-based modeling of allosteric residue potentials are employed for a detailed analysis of allosteric interaction networks and identification of conformational communication switches. We found that allosteric interactions between the Hsp90, the client-bound Hsp70 and Hop cochaperone can define two allosteric residue clusters that control client recruitment in which the intrinsic Hsp70 allostery is exploited to mediate integration of the Hsp70-bound client into the Hsp90 chaperone system. The results suggest a model of dynamics-driven allostery that enables efficient client recruitment and loading through allosteric couplings between intermolecular interfaces and communication switch centers. This study showed that the Hsp90 interactions with client proteins may operate under dynamic-based allostery in which ensembles of preexisting conformational states and intrinsic allosteric pathways present in the Hsp90 and Hsp70 chaperones can be exploited for recognition and integration of substrate proteins.
211. Allosteric Determinants of the SARS-CoV-2 Spike Protein Binding with Nanobodies: Examining Mechanisms of Mutational Escape and Sensitivity of the Omicron Variant.
     Verkhivker G. Int J Mol Sci. 2022 23, 4, 2172. doi: 10.3390/ijms23042172
     Abstract

     Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against the SARS-CoV-2 virus and resilience against mutational escape. In this study, we performed a comprehensive computational analysis of the SARS-CoV-2 spike trimer complexes with single nanobodies Nb6, VHH E, and complex with VHH E/VHH V nanobody combination. We combined coarse-grained and all-atom molecular simulations and collective dynamics analysis with binding free energy scanning, perturbation-response scanning, and network centrality analysis to examine mechanisms of nanobody-induced allosteric modulation and cooperativity in the SARS-CoV-2 spike trimer complexes with these nanobodies. By quantifying energetic and allosteric determinants of the SARS-CoV-2 spike protein binding with nanobodies, we also examined nanobody-induced modulation of escaping mutations and the effect of the Omicron variant on nanobody binding. The mutational scanning analysis supported the notion that E484A mutation can have a significant detrimental effect on nanobody binding and result in Omicron-induced escape from nanobody neutralization. Our findings showed that SARS-CoV-2 spike protein might exploit the plasticity of specific allosteric hotspots to generate escape mutants that alter response to binding without compromising activity. The network analysis supported these findings showing that VHH E/VHH V nanobody binding can induce long-range couplings between the cryptic binding epitope and ACE2-binding site through a broader ensemble of communication paths that is less dependent on specific mediating centers and therefore may be less sensitive to mutational perturbations of functional residues. The results suggest that binding affinity and long-range communications of the SARS-CoV-2 complexes with nanobodies can be determined by structurally stable regulatory centers and conformationally adaptable hotspots that are allosterically coupled and collectively control resilience to mutational escape.
212. Conformational Flexibility and Local Frustration in the Functional States of the SARS-CoV-2 Spike B.1.1.7 and B.1.351 Variants: Mutation-Induced Allosteric Modulation Mechanism of Functional Dynamics and Protein Stability.
     Verkhivker G. Int J Mol Sci. 2022 23, 3, 1646. doi: 10.3390/ijms23031646.
     Abstract

     Structural and functional studies of the SARS-CoV-2 spike proteins have recently determined distinct functional states of the B.1.1.7 and B.1.351 spike variants, providing a molecular framework for understanding the mechanisms that link the effect of mutations with the enhanced virus infectivity and transmissibility. A detailed dynamic and energetic analysis of these variants was undertaken in the present work to quantify the effects of different mutations on functional conformational changes and stability of the SARS-CoV-2 spike protein. We employed the efficient and accurate coarse-grained (CG) simulations of multiple functional states of the D614G mutant, B.1.1.7 and B.1.351 spike variants to characterize conformational dynamics of the SARS-CoV-2 spike proteins and identify dynamic signatures of the functional regions that regulate transitions between the closed and open forms. By combining molecular simulations with full atomistic reconstruction of the trajectories and the ensemble-based mutational frustration analysis, we characterized how the intrinsic flexibility of specific spike regions can control functional conformational changes required for binding with the host-cell receptor. Using the residue-based mutational scanning of protein stability, we determined protein stability hotspots and identified potential energetic drivers favoring the receptor-accessible open spike states for the B.1.1.7 and B.1.351 spike variants. The results suggested that modulation of the energetic frustration at the inter-protomer interfaces can serve as a mechanism for allosteric couplings between mutational sites and the inter-protomer hinges of functional motions. The proposed mechanism of mutation-induced energetic frustration may result in greater adaptability and the emergence of multiple conformational states in the open form. This study suggested that SARS-CoV-2 B.1.1.7 and B.1.351 variants may leverage the intrinsic plasticity of functional regions in the spike protein for mutation-induced modulation of protein dynamics and allosteric regulation to control binding with the host cell receptor.

2021

183. The Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614 Mutant: Conformational Plasticity and Frustration-Driven Allostery as Energetic Drivers of Highly Transmissible Spike Variant.
     Verkhivker G, Agajanian S, Kassab R, Krishnan K. Biorxiv. 2021. DOI: 10.1101/2021.12.09.471953
     Abstract

     The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern(VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model which can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the inter-protomer hinge modulate the inter-domain interactions, global mobility change and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the inter-protomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.
184. Allosteric Control of Structural Mimicry and Mutational Escape in the SARS-CoV-2 Spike Protein Complexes with the ACE2 Decoys and Miniprotein Inhibitors: A Network-Based Approach for Mutational Profiling of Binding and Signaling.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. J Chem Inf Model. 2021, 61, 10, 5172-5191. doi: 10.1021/acs.jcim.1c00766.
     Abstract

     We developed a computational framework for comprehensive and rapid mutational scanning of binding energetics and residue interaction networks in the SARS-CoV-2 spike protein complexes. Using this approach, we integrated atomistic simulations and conformational landscaping of the SARS-CoV-2 spike protein complexes with ensemble-based mutational screening and network modeling to characterize mechanisms of structure–functional mimicry and resilience toward mutational escape by the ACE2 protein decoy and de novo designed miniprotein inhibitors. A detailed analysis of structural plasticity of the SARS-CoV-2 spike proteins obtained from atomistic simulations of conformational landscapes and sequence-based profiling of the disorder propensities revealed the intrinsically flexible regions that harbor key functional sites targeted by circulating variants. The conservation of collective dynamics in the SARS-CoV-2 spike protein complexes showed that mutational escape positions are important for modulation of functional motions and that mutational changes in these sites can alter allosteric interaction networks. Through mutational profiling of binding and allosteric propensities in the SARS-CoV-2 spike protein complexes, we identified the key binding and regulatory hotspots that collectively determine functional response and resilience of miniproteins to mutational variants. The results suggest that binding affinities and allosteric signatures of the SARS-CoV-2 complexes can be determined by dynamic crosstalk between structurally stable regulatory centers and conformationally adaptable allosteric hotspots that collectively control the resilience toward mutational escape. This may underlie a mechanism in which moderate perturbations in the mutational escape positions can induce global allosteric changes and alter functional protein response by modulating signaling in the residue interaction networks.
185. Atomistic Simulations and In Silico Mutational Profiling of Protein Stability and Binding in the SARS-CoV-2 Spike Protein Complexes with Nanobodies: Molecular Determinants of Mutational Escape Mechanisms.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. ACS Omega. 2021, 6, 40, 26354-26371. doi: 10.1021/acsomega.1c03558.
     Abstract

     Structure-functional studies have recently revealed a spectrum of diverse high-affinity nanobodies with efficient neutralizing capacity against SARS-CoV-2 virus and resilience against mutational escape. In this study, we combine atomistic simulations with the ensemble-based mutational profiling of binding for the SARS-CoV-2 S-RBD complexes with a wide range of nanobodies to identify dynamic and binding affinity fingerprints and characterize the energetic determinants of nanobody-escaping mutations. Using an in silico mutational profiling approach for probing the protein stability and binding, we examine dynamics and energetics of the SARS-CoV-2 complexes with single nanobodies Nb6 and Nb20, VHH E, a pair combination VHH E + U, a biparatopic nanobody VHH VE, and a combination of the CC12.3 antibody and VHH V/W nanobodies. This study characterizes the binding energy hotspots in the SARS-CoV-2 protein and complexes with nanobodies providing a quantitative analysis of the effects of circulating variants and escaping mutations on binding that is consistent with a broad range of biochemical experiments. The results suggest that mutational escape may be controlled through structurally adaptable binding hotspots in the receptor-accessible binding epitope that are dynamically coupled to the stability centers in the distant binding epitope targeted by VHH U/V/W nanobodies. This study offers a plausible mechanism in which through cooperative dynamic changes, nanobody combinations and biparatopic nanobodies can elicit the increased binding affinity response and yield resilience to common escape mutants.
186. Making the invisible visible: Toward structural characterization of allosteric states, interaction networks, and allosteric regulatory mechanisms in protein kinases.
     Verkhivker G. Curr Opin Struct Biol. 2021, 71, 71-78. doi: 10.1016/j.sbi.2021.06.002. Epub 2021 Jul 5. Review. PubMed PMID: 34237520.
     Abstract

     Despite the established view of protein kinases as dynamic and versatile allosteric regulatory machines, our knowledge of allosteric functional states, allosteric interaction networks, and the intrinsic folding energy landscapes is surprisingly limited. We discuss the latest developments in structural characterization of allosteric molecular events underlying protein kinase dynamics and functions using structural, biophysical, and computational biology approaches. The recent studies highlighted progress in making the invisible aspects of protein kinase ‘life’ visible, including the determination of hidden allosteric states and mapping of allosteric energy landscapes, discovery of new mechanisms underlying ligand-induced modulation of allosteric activity, evolutionary adaptation of kinase allostery, and characterization of allosteric interaction networks as the intrinsic driver of kinase adaptability and signal transmission in the regulatory assemblies.
187. Dimeric allostery mechanism of the plant circadian clock photoreceptor Zeitlupe.
     Trozzi F, Wang F, Verkhivker G, Zoltowski B.D., Tao P. PLoS Comput Biol. 2021, 17, 7, e1009168. doi: 10.1371/journal.pcbi.1009168.
     Abstract

     In Arabidopsis thaliana, the Light-Oxygen-Voltage (LOV) domain containing protein ZEITLUPE (ZTL) integrates light quality, intensity, and duration into regulation of the circadian clock. Recent structural and biochemical studies of ZTL indicate that the protein diverges from other members of the LOV superfamily in its allosteric mechanism, and that the divergent allosteric mechanism hinges upon conservation of two signaling residues G46 and V48 that alter dynamic motions of a Gln residue implicated in signal transduction in all LOV proteins. Here, we delineate the allosteric mechanism of ZTL via an integrated computational approach that employs atomistic simulations of wild type and allosteric variants of ZTL in the functional dark and light states, together with Markov state and supervised machine learning classification models. This approach has unveiled key factors of the ZTL allosteric mechanisms, and identified specific interactions and residues implicated in functional allosteric changes. The final results reveal atomic level insights into allosteric mechanisms of ZTL function that operate via a non-trivial combination of population-shift and dynamics-driven allosteric pathways.
188. Dissecting Molecular Determinants of Mutational Escape Mechanisms in the SARS-CoV-2 Spike Protein Complexes with Nanobodies: Atomistic Simulations and Ensemble-Based Deep Mutational Scanning of Protein Stability and Binding Interactions.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. Preprints. 2021. doi: 10.20944/preprints202107.0295.v1
     Abstract

     Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against SARS-CoV-2 virus and resilience against mutational escape. In this work, we combined atomistic simulations and conformational dynamics analysis with the ensemble-based mutational profiling of binding interactions for a diverse panel of SARS-CoV-2 spike complexes with nanobodies. Using this computational toolkit, we identified dynamic signatures and binding affinity fingerprints for the SARS-CoV-2 spike protein complexes with nanobodies Nb6 and Nb20, VHH E, a pair combination VHH E+U, a biparatopic nanobody VHH VE, and a combination of CC12.3 antibody and VHH V/W nanobodies. Through ensemble-based deep mutational profiling of stability and binding affinities, we identify critical hotspots and characterize molecular mechanisms of SARS-CoV-2 spike protein binding with single ultra-potent nanobodies, nanobody cocktails and biparatopic nanobodies. By quantifying dynamic and energetic determinants of the SARS-CoV-2 S binding with nanobodies, we also examine the effects of circulating variants and escaping mutations. We found that mutational escape mechanisms may be controlled through structurally and energetically adaptable binding hotspots located in the host receptor-accessible binding epitope that are dynamically coupled to the stability centers in the distant epitope targeted by VHH U/V/W nanobodies. The results of this study suggested a mechanism in which through cooperative dynamic changes, nanobody combinations and biparatopic nanobody can modulate the global protein response and induce the increased resilience to common escape mutants.
189. Dynamic Profiling of Binding and Allosteric Propensities of the SARS-CoV-2 Spike Protein with Different Classes of Antibodies: Mutational and Perturbation-Based Scanning Reveals the Allosteric Duality of Functionally Adaptable Hotspots.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. J Chem Theory Comput. 2021, 17, 7, 4578-4598. doi: 10.1021/acs.jctc.1c00372.
     Abstract

     The functional adaptability and conformational plasticity of SARS-CoV-2 spike proteins allow for the efficient modulation of complex phenotypic responses to the host receptor and antibodies. In this study, we combined atomistic simulations with mutational and perturbation-based scanning approaches to examine binding mechanisms of the SARS-CoV-2 spike proteins with three different classes of antibodies. The ensemble-based profiling of binding and allosteric propensities of the SARS-CoV-2 spike protein residues showed that these proteins can work as functionally adaptable and allosterically regulated machines. Conformational dynamics analysis revealed that binding-induced modulation of soft modes can elicit the unique protein response to different classes of antibodies. Mutational scanning heatmaps and sensitivity analysis revealed the binding energy hotspots for different classes of antibodies that are consistent with the experimental deep mutagenesis, showing that differences in the binding affinity caused by global circulating variants in spike positions K417, E484, and N501 are relatively moderate and may not fully account for the observed antibody resistance effects. Through functional dynamics analysis and perturbation-response scanning of the SARS-CoV-2 spike protein residues in the unbound form and antibody-bound forms, we examine how antibody binding can modulate allosteric propensities of spike protein residues and determine allosteric hotspots that control signal transmission and global conformational changes. These results show that residues K417, E484, and N501 targeted by circulating mutations correspond to a group of versatile allosteric centers in which small perturbations can modulate collective motions, alter the global allosteric response, and elicit binding resistance. We suggest that the SARS-CoV-2 S protein may exploit the plasticity of specific allosteric hotspots to generate escape mutants that alter the response to antibody binding without compromising the activity of the spike protein.
190. Atomistic Simulations and Deep Mutational Scanning of Protein Stability and Binding Interactions in the SARS-CoV-2 Spike Protein Complexes with Nanobodies: Molecular Determinants of Mutational Escape Mechanisms.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. ACS Omega. 2021, 6, 40, 26354–26371. doi: 10.1021/acsomega.1c03558.
     Abstract

     Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against SARS-CoV-2 virus and resilience against mutational escape. In this work, we combined atomistic simulations and conformational dynamics analysis with the ensemble-based mutational profiling of binding interactions for a diverse panel of SARS-CoV-2 spike complexes with nanobodies. Using this computational toolkit we identified dynamic signatures and binding affinity fingerprints for the SARS-CoV-2 spike protein complexes with nanobodies Nb6 and Nb20, VHH E, a pair combination VHH E+U, a biparatopic nanobody VHH VE, and a combination of CC12.3 antibody and VHH V/W nanobodies. Through ensemble-based deep mutational profiling of stability and binding affinities, we identify critical hotspots and characterize molecular mechanisms of SARS-CoV-2 spike protein binding with single ultra-potent nanobodies, nanobody cocktails and biparatopic nanobodies. By quantifying dynamic and energetic determinants of the SARS-CoV-2 S binding with nanobodies, we also examine the effects of circulating variants and escaping mutations. We found that mutational escape mechanisms may be controlled through structurally and energetically adaptable binding hotspots located in the host receptor-accessible binding epitope that are dynamically coupled to the stability centers in the distant epitope targeted by VHH U/V/W nanobodies. The results of this study suggested a mechanism in which through cooperative dynamic changes, nanobody combinations and biparatopic nanobody can modulate the global protein response and induce the increased resilience to common escape mutants.
191. Computational analysis of protein stability and allosteric interaction networks in distinct conformational forms of the SARS-CoV-2 spike D614G mutant: reconciling functional mechanisms through allosteric model of spike regulation.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. J Biomol Struct Dyn. 2021,1-18. doi: 10.1080/07391102.2021.
     Abstract

     In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis with network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike engine. By combining functional dynamics analysis and ensemble-based alanine scanning of the SARS-CoV-2 spike proteins we found that the D614G mutation can improve stability of the spike protein in both closed and open forms, but shifting thermodynamic preferences towards the open mutant form. Our results revealed that the D614G mutation can promote the increased number of stable communities and allosteric hub centers in the open form by reorganizing and enhancing the stability of the S1-S2 inter-domain interactions and restricting mobility of the S1 regions. This study provides atomistic-based view of allosteric communications in the SARS-CoV-2 spike proteins, suggesting that the D614G mutation can exert its primary effect through allosterically induced changes on stability and communications in the residue interaction networks.
192. Landscape-Based Mutational Sensitivity Cartography and Network Community Analysis of the SARS-CoV-2 Spike Protein Structures: Quantifying Functional Effects of the Circulating D614G Variant.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. ACS Omega. 2021, 6, 24,16216-16233. doi: 10.1021/acsomega.1c02336.
     Abstract

     We developed and applied a computational approach to simulate functional effects of the global circulating mutation D614G of the SARS-CoV-2 spike protein. All-atom molecular dynamics simulations are combined with deep mutational scanning and analysis of the residue interaction networks to investigate conformational landscapes and energetics of the SARS-CoV-2 spike proteins in different functional states of the D614G mutant. The results of conformational dynamics and analysis of collective motions demonstrated that the D614 site plays a key regulatory role in governing functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of protein residues, we identified the stability hotspots in the SARS-CoV-2 spike structures of the mutant trimers. The results suggest that the D614G mutation can induce the increased stability of the open form acting as a driver of conformational changes, which may result in the increased exposure to the host receptor and promote infectivity of the virus. The network community analysis of the SARS-CoV-2 spike proteins showed that the D614G mutation can enhance long-range couplings between domains and strengthen the interdomain interactions in the open form, supporting the reduced shedding mechanism. This study provides the landscape-based perspective and atomistic view of the allosteric interactions and stability hotspots in the SARS-CoV-2 spike proteins, offering a useful insight into the molecular mechanisms underpinning functional effects of the global circulating mutations.
193. Deep Mutational Scanning of Dynamic Interaction Networks in the SARS-CoV-2 Spike Protein Complexes: Allosteric Hotspots Control Functional Mimicry and Resilience to Mutational Escape.
     Verkhivker, G. J. Chem. Inf. Model. 2021, 61, 10, 5172–5191. doi: 10.1101/2021.06.15.448568
     Abstract

     We develop a computational approach for deep mutational scanning of residue interaction networks in the SARS-CoV-2 spike protein complexes to characterize mechanisms of functional mimicry and resilience to mutational escape by miniprotein inhibitors. Using a dynamic mutational profiling and sensitivity analysis of protein stability, binding interactions and global network parameters describing allosteric signaling, we identify regulatory hotspots in the SARS-CoV-2 S complexes with the ACE2 host receptor and ultra-potent miniproteins. The results revealed that global circulating variants are associated with allosteric control points that are dynamically coupled to structural stability hotspots. In this mechanism, variant-induced perturbations of flexible allosteric sites can result in global network changes and elicit specific protein responses. The binding affinity fingerprints and allosteric signatures of the SARS-CoV-2 complexes with miniproteins are determined by a dynamic cross-talk between regulatory control points and conformationally adaptable allosteric hotspots that collectively control structure-functional mimicry, signal transmission and resilience to mutational escape.
194. Landscape-Based Mutational Sensitivity Cartography and Network Community Analysis of the SARS-CoV-2 Spike Protein Structures: Quantifying Functional Effects of the Circulating Variants.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. ACS Omega. 2021, 6, 24, 16216–16233. doi: 10.1021/acsomega.1c02336.
     Abstract

     We developed and applied a computational approach to simulate functional effects of the global circulating mutation D614G of the SARS-CoV-2 spike protein. All-atom molecular dynamics simulations are combined with deep mutational scanning and analysis of the residue interaction networks to investigate conformational landscapes and energetics of the SARS-CoV-2 spike proteins in different functional states of the D614G mutant. The results of conformational dynamics and analysis of collective motions demonstrated that the D614 site plays a key regulatory role in governing functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of protein residues, we identified the stability hotspots in the SARS-CoV-2 spike structures of the mutant trimers. The results suggest that the D614G mutation can induce the increased stability of the open form acting as a driver of conformational changes, which may result in the increased exposure to the host receptor and promote infectivity of the virus. The network community analysis of the SARS-CoV-2 spike proteins showed that the D614G mutation can enhance long-range couplings between domains and strengthen the interdomain interactions in the open form, supporting the reduced shedding mechanism. This study provides the landscape-based perspective and atomistic view of the allosteric interactions and stability hotspots in the SARS-CoV-2 spike proteins, offering a useful insight into the molecular mechanisms underpinning functional effects of the global circulating mutations.
195. Comparative Perturbation-Based Modeling of the SARS-CoV-2 Spike Protein Binding with Host Receptor and Neutralizing Antibodies: Structurally Adaptable Allosteric Communication Hotspots Define Spike Sites Targeted by Global Circulating Mutations.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. Biochemistry. 2021, 60, 19, 1459-1484. doi: 10.1021/acs.biochem.1c00139.
     Abstract

     In this study, we used an integrative computational approach to examine molecular mechanisms and determine functional signatures underlying the role of functional residues in the SARS-CoV-2 spike protein that are targeted by novel mutational variants and antibody-escaping mutations. Atomistic simulations and functional dynamics analysis are combined with alanine scanning and mutational sensitivity profiling of the SARS-CoV-2 spike protein complexes with the ACE2 host receptor and the REGN-COV2 antibody cocktail(REG10987+REG10933). Using alanine scanning and mutational sensitivity analysis, we have shown that K417, E484, and N501 residues correspond to key interacting centers with a significant degree of structural and energetic plasticity that allow mutants in these positions to afford the improved binding affinity with ACE2. Through perturbation-based network modeling and community analysis of the SARS-CoV-2 spike protein complexes with ACE2, we demonstrate that E406, N439, K417, and N501 residues serve as effector centers of allosteric interactions and anchor major intermolecular communities that mediate long-range communication in the complexes. The results provide support to a model according to which mutational variants and antibody-escaping mutations constrained by the requirements for host receptor binding and preservation of stability may preferentially select structurally plastic and energetically adaptable allosteric centers to differentially modulate collective motions and allosteric interactions in the complexes with the ACE2 enzyme and REGN-COV2 antibody combination. This study suggests that the SARS-CoV-2 spike protein may function as a versatile and functionally adaptable allosteric machine that exploits the plasticity of allosteric regulatory centers to fine-tune response to antibody binding without compromising the activity of the spike protein.
196. Integrated Biophysical Modeling of the SARS-CoV-2 Spike Protein Binding and Allosteric Interactions with Antibodies.
     Verkhivker G, Di Paola L. J Phys Chem B. 2021, 125, 18, 4596-4619. doi: 10.1021/acs.jpcb.1c00395.
     Abstract

     Structural and biochemical studies of the severe acute respiratory syndrome (SARS)-CoV-2 spike glycoproteins and complexes with highly potent antibodies have revealed multiple conformation-dependent epitopes highlighting conformational plasticity of spike proteins and capacity for eliciting specific binding and broad neutralization responses. In this study, we used coevolutionary analysis, molecular simulations, and perturbation-based hierarchical network modeling of the SARS-CoV-2 spike protein complexes with a panel of antibodies targeting distinct epitopes to explore molecular mechanisms underlying binding-induced modulation of dynamics and allosteric signaling in the spike proteins. Through coevolutionary analysis of the SARS-CoV-2 spike proteins, we identified highly coevolving hotspots and functional clusters that enable a functional cross-talk between distant allosteric regions in the SARS-CoV-2 spike complexes with antibodies. Coarse-grained and all-atom molecular dynamics simulations combined with mutational sensitivity mapping and perturbation-based profiling of the SARS-CoV-2 receptor-binding domain (RBD) complexes with CR3022 and CB6 antibodies enabled a detailed validation of the proposed approach and an extensive quantitative comparison with the experimental structural and deep mutagenesis scanning data. By combining in silico mutational scanning, perturbation-based modeling, and network analysis of the SARS-CoV-2 spike trimer complexes with H014, S309, S2M11, and S2E12 antibodies, we demonstrated that antibodies can incur specific and functionally relevant changes by modulating allosteric propensities and collective dynamics of the SARS-CoV-2 spike proteins. The results provide a novel insight into regulatory mechanisms of SARS-CoV-2 S proteins showing that antibody-escaping mutations can preferentially target structurally adaptable energy hotspots and allosteric effector centers that control functional movements and allosteric communication in the complexes.
197. Dynamic Profiling of Binding and Allosteric Propensities of the SARS-CoV-2 Spike Protein with Different Classes of Antibodies: Mutational and Perturbation-Based Scanning Reveal Allosteric Duality of Functionally Adaptable Hotspots.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. J. Chem.Theory Comput. 2021, 17, 7, 4578–4598. doi: 10.1021/acs.jctc.1c00372.
     Abstract

     Structural and biochemical studies of the SARS-CoV-2 spike complexes with highly potent antibodies have revealed multiple conformation-dependent epitopes and a broad range of recognition modes linked to different neutralization responses In this study, we combined atomistic simulations with mutational and perturbation-based scanning approaches to perform in silico profiling of binding and allosteric propensities of the SARS-CoV-2 spike protein residues in complexes with B38, P2B-2F6, EY6A and S304 antibodies representing three different classes. Conformational dynamics analysis revealed that binding-induced modulation of soft modes can elicit the unique protein response to different classes of antibodies. Mutational scanning heatmaps and sensitivity analysis revealed the binding energy hotspots for different classes of antibodies that are consistent with the experimental deep mutagenesis, showing that differences in the binding affinity caused by global circulating variants in spike positions K417, E484 and N501 are relatively moderate and may not fully account for the observed antibody resistance effects. Through functional dynamics analysis and perturbation-response scanning of the SARS-CoV-2 spike protein residues in the unbound form and antibody-bound forms, we examine how antibody binding can modulate allosteric propensities of spike protein residues and determine allosteric hotspots that control signal transmission and global conformational changes. These results show that residues K417, E484, and N501 targeted by circulating mutations correspond to a group of versatile allosteric centers in which small perturbations can modulate collective motions, alter the global allosteric response and elicit binding resistance. We suggest that SARS-CoV-2 S protein may exploit plasticity of specific allosteric hotspots to generate escape mutants that alter response to antibody binding without compromising activity of the spike protein.
198. Comparative Perturbation-Based Modeling of the SARS-CoV-2 Spike Protein Binding with Host Receptor and Neutralizing Antibodies : Structurally Adaptable Allosteric Communication Hotspots Define Spike Sites Targeted by Global Circulating Mutations.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. Biochemistry. 2021, 60, 19, 1459–1484. doi: 10.1021/acs.biochem.1c00139
     Abstract

     In this study, we used an integrative computational approach focused on comparative perturbation-based modeling to examine molecular mechanisms and determine functional signatures underlying role of functional residues in the SARS-CoV-2 spike protein that are targeted by novel mutational variants and antibody-escaping mutations. Atomistic simulations and functional dynamics analysis are combined with alanine scanning and mutational sensitivity profiling for the SARS-CoV-2 spike protein complexes with the ACE2 host receptor are REGN-COV2 antibody cocktail (REG10987+REG10933). Using alanine scanning and mutational sensitivity analysis, we have shown that K417, E484 and N501 residues correspond to key interacting centers with a significant degree of structural and energetic plasticity that allow mutants in these positions to afford the improved binding affinity with ACE2. Through perturbation-based network modeling and community analysis of the SARS-CoV-2 spike protein complexes with ACE2 we demonstrate that E406, N439, K417 and N501 residues serve as effector centers of allosteric interactions and anchor major inter-molecular communities that mediate long-range communication in the complexes. The results provide support to a model according to which mutational variants and antibody-escaping mutations constrained by the requirements for host receptor binding and preservation of stability may preferentially select structurally plastic and energetically adaptable allosteric centers to differentially modulate collective motions and allosteric interactions in the complexes with the ACE2 enzyme and REGN-COV2 antibody combination. This study suggests that SARS-CoV-2 spike protein may function as a versatile and functionally adaptable allosteric machine that exploits plasticity of allosteric regulatory centers to fine-tune response to antibody binding without compromising activity of the spike protein.
199. Computational Analysis of Protein Stability and Allosteric Interaction Networks in Distinct Conformational Forms of the SARS-CoV-2 Spike D614G Mutant: Reconciling Functional Mechanisms through Allosteric Model of Spike Regulation.
     Verkhivker G, Agajanian S, Oztas D, Gupta G. J Biomol Struct Dyn. 2021, 1-18. doi: 10.1080/07391102.2021.1933594.
     Abstract

     Structural and biochemical studies SARS-CoV-2 spike mutants with the enhanced infectivity have attracted significant attention and offered several mechanisms to explain the experimental data. The development of a unified view and a working model which is consistent with the diverse experimental data is an important focal point of the current work. In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis along with network-based community analysis to simulate structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. The results demonstrated that the D614 position anchors a key regulatory cluster that dictates functional transitions between open and closed states. Using molecular simulations and mutational sensitivity analysis of the SARS-CoV-2 spike proteins we showed that the D614G mutation can improve stability of the spike protein in both closed and open forms, but shifting thermodynamic preferences towards the open mutant form. The results offer support to the reduced shedding mechanism of S1 domain as a driver of the increased infectivity triggered by the D614G mutation. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike engine. By employing network community analysis of the SARS-CoV-2 spike proteins, our results revealed that the D614G mutation can promote the increased number of stable communities and allosteric hub centers in the open form by reorganizing and enhancing the stability of the S1-S2 inter-domain interactions and restricting mobility of the S1 regions. This study provides atomistic-based view of the allosteric interactions and communications in the SARS-CoV-2 spike proteins, suggesting that the D614G mutation can exert its primary effect through allosterically induced changes on stability and communications in the residue interaction networks.
200. Dynamic Network Modeling of Allosteric Interactions and Communication Pathways in the SARS-CoV-2 Spike Trimer Mutants: Differential Modulation of Conformational Landscapes and Signal Transmission via Cascades of Regulatory Switches.
     Verkhivker G, Di Paola L. J Phys Chem B. 2021,125, 3, 850-873. doi: 10.1021/acs.jpcb.0c10637.
     Abstract

     The rapidly growing body of structural and biochemical studies of the SARS-CoV-2 spike glycoprotein has revealed a variety of distinct functional states with radically different arrangements of the receptor-binding domain, highlighting a remarkable function-driven conformational plasticity and adaptability of the spike proteins. In this study, we examined molecular mechanisms underlying conformational and dynamic changes in the SARS-CoV-2 spike mutant trimers through the lens of dynamic analysis of allosteric interaction networks and atomistic modeling of signal transmission. Using an integrated approach that combined coarse-grained molecular simulations, protein stability analysis, and perturbation-based modeling of residue interaction networks, we examined how mutations in the regulatory regions of the SARS-CoV-2 spike protein can differentially affect dynamics and allosteric signaling in distinct functional states. The results of this study revealed key functional regions and regulatory centers that govern collective dynamics, allosteric interactions, and control signal transmission in the SARS-CoV-2 spike proteins. We found that the experimentally confirmed regulatory hotspots that dictate dynamic switching between conformational states of the SARS-CoV-2 spike protein correspond to the key hinge sites and global mediating centers of the allosteric interaction networks. The results of this study provide a novel insight into allosteric regulatory mechanisms of SARS-CoV-2 spike proteins showing that mutations at the key regulatory positions can differentially modulate distribution of states and determine topography of signal communication pathways operating through state-specific cascades of control switch points. This analysis provides a plausible strategy for allosteric probing of the conformational equilibrium and therapeutic intervention by targeting specific hotspots of allosteric interactions and communications in the SARS-CoV-2 spike proteins.
201. Coevolutionary Analysis and Perturbation-Based Network Modeling of the SARS-CoV-2 Spike Protein Complexes with Antibodies: Binding-Induced Control of Dynamics, Allosteric Interactions and Signaling.
     Verkhivker G, Di Paola L. J. Phys. Chem. B. 2021, 125, 18, 4596–4619. doi: 10.1101/2021.01.19.427320
     Abstract

     The structural and biochemical studies of the SARS-CoV-2 spike glycoproteins and complexes with highly potent antibodies have revealed multiple conformation-dependent epitopes highlighting the link between conformational plasticity of spike proteins and capacity for eliciting specific binding and broad neutralization responses. In this study, we used coevolutionary analysis, molecular simulations, and perturbation-based hierarchical network modeling of the SARS-CoV-2 S complexes with H014, S309, S2M11 and S2E12 antibodies targeting distinct epitopes to explore molecular mechanisms underlying binding-induced modulation of dynamics, stability and allosteric signaling in the spike protein trimers. The results of this study revealed key regulatory centers that can govern allosteric interactions and communications in the SARS-CoV-2 spike proteins. Through coevolutionary analysis of the SARS-CoV-2 spike proteins, we identified highly coevolving hotspots and functional clusters forming coevolutionary networks. The results revealed significant coevolutionary couplings between functional regions separated by the medium-range distances which may help to facilitate a functional cross-talk between distant allosteric regions in the SARS-CoV-2 spike complexes with antibodies. We also discovered a potential mechanism by which antibody-specific targeting of coevolutionary centers can allow for efficient modulation of allosteric interactions and signal propagation between remote functional regions. Using a hierarchical network modeling and perturbation-response scanning analysis, we demonstrated that binding of antibodies could leverage direct contacts with coevolutionary hotspots to allosterically restore and enhance couplings between spatially separated functional regions, thereby protecting the spike apparatus from membrane fusion. The results of this study also suggested that antibody binding can induce a switch from a moderately cooperative population-shift mechanism, governing structural changes of the ligand-free SARS-CoV-2 spike protein, to antibody-induced highly cooperative mechanism that can better withstand mutations in the functional regions without significant deleterious consequences for protein function. This study provides a novel insight into allosteric regulatory mechanisms of SARS-CoV-2 S proteins, showing that antibodies can modulate allosteric interactions and signaling of spike proteins, providing a plausible strategy for therapeutic intervention by targeting specific hotspots of allosteric interactions in the SARS-CoV-2 proteins.

2020

164. Molecular Simulations and Network Modeling Reveal an Allosteric Signaling in the SARS-CoV-2 Spike Proteins.
     Verkhivker G. J Proteome Res. 2020, 19, 11, 4587-4608. doi: 10.1021/acs.jproteome.0c00654.
     Abstract

     The development of computational strategies for the quantitative characterization of the functional mechanisms of SARS-CoV-2 spike proteins is of paramount importance in efforts to accelerate the discovery of novel therapeutic agents and vaccines combating the COVID-19 pandemic. Structural and biophysical studies have recently characterized the conformational landscapes of the SARS-CoV-2 spike glycoproteins in the prefusion form, revealing a spectrum of stable and more dynamic states. By employing molecular simulations and network modeling approaches, this study systematically examined functional dynamics and identified the regulatory centers of allosteric interactions for distinct functional states of the wild-type and mutant variants of the SARS-CoV-2 prefusion spike trimer. This study presents evidence that the SARS-CoV-2 spike protein can function as an allosteric regulatory engine that fluctuates between dynamically distinct functional states. Perturbation-based modeling of the interaction networks revealed a key role of the cross-talk between the effector hotspots in the receptor binding domain and the fusion peptide proximal region of the SARS-CoV-2 spike protein. The results have shown that the allosteric hotspots of the interaction networks in the SARS-CoV-2 spike protein can control the dynamic switching between functional conformational states that are associated with virus entry to the host receptor. This study offers a useful and novel perspective on the underlying mechanisms of the SARS-CoV-2 spike protein through the lens of allosteric signaling as a regulatory apparatus of virus transmission that could open up opportunities for targeted allosteric drug discovery against SARS-CoV-2 proteins and contribute to the rapid response to the current and potential future pandemic scenarios.
165. Coevolution, Dynamics and Allostery Conspire in Shaping Cooperative Binding and Signal Transmission of the SARS-CoV-2 Spike Protein with Human Angiotensin-Converting Enzyme 2. 
     Verkhivker G. Int J Mol Sci. 2020, 21, 21, 8268. doi: 10.3390/ijms21218268.
     Abstract

     Binding to the host receptor is a critical initial step for the coronavirus SARS-CoV-2 spike protein to enter into target cells and trigger virus transmission. A detailed dynamic and energetic view of the binding mechanisms underlying virus entry is not fully understood and the consensus around the molecular origins behind binding preferences of SARS-CoV-2 for binding with the angiotensin-converting enzyme 2 (ACE2) host receptor is yet to be established. In this work, we performed a comprehensive computational investigation in which sequence analysis and modeling of coevolutionary networks are combined with atomistic molecular simulations and comparative binding free energy analysis of the SARS-CoV and SARS-CoV-2 spike protein receptor binding domains with the ACE2 host receptor. Different from other computational studies, we systematically examine the molecular and energetic determinants of the binding mechanisms between SARS-CoV-2 and ACE2 proteins through the lens of coevolution, conformational dynamics, and allosteric interactions that conspire to drive binding interactions and signal transmission. Conformational dynamics analysis revealed the important differences in mobility of the binding interfaces for the SARS-CoV-2 spike protein that are not confined to several binding hotspots, but instead are broadly distributed across many interface residues. Through coevolutionary network analysis and dynamics-based alanine scanning, we established linkages between the binding energy hotspots and potential regulators and carriers of signal communication in the virus-host receptor complexes. The results of this study detailed a binding mechanism in which the energetics of the SARS-CoV-2 association with ACE2 may be determined by cumulative changes of a number of residues distributed across the entire binding interface. The central findings of this study are consistent with structural and biochemical data and highlight drug discovery challenges of inhibiting large and adaptive protein-protein interfaces responsible for virus entry and infection transmission.
166. Impact of Early Pandemic Stage Mutations on Molecular Dynamics of SARS-CoV-2 Mpro.
     Sheik Amamuddy O, Verkhivker GM, Tastan Bishop Ö. J Chem Inf Model. 2020, 60, 10, 5080-5102. doi: 10.1021/acs.jcim.0c00634.
     Abstract

     A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (Mpro), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of Mpro behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant Mpro dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, Rg, averaged betweenness centrality, and geometry calculations. The results showed that SARS-CoV-2 Mpro essentially behaves in a similar manner to its SAR-CoV homolog. However, we report the following new findings from the variants: (1) Residues GLY15, VAL157, and PRO184 have mutated more than once in SARS CoV-2; (2) the D48E variant has lead to a novel “TSEEMLN”” loop at the binding pocket; (3) inactive apo Mpro does not show signs of dissociation in 100 ns MD; (4) a non-canonical pose for PHE140 widens the substrate binding surface; (5) dual allosteric pockets coinciding with various stabilizing and functional components of the substrate binding pocket were found to display correlated compaction dynamics; (6) high betweenness centrality values for residues 17 and 128 in all Mpro samples suggest their high importance in dimer stability—one such consequence has been observed for the M17I mutation whereby one of the N-fingers was highly unstable. (7) Independent coarse-grained Monte Carlo simulations suggest a relationship between the rigidity/mutability and enzymatic function. Our entire approach combining database preparation, variant retrieval, homology modeling, dynamic residue network (DRN), relevant conformation retrieval from 1-D kernel density estimates from reaction coordinates to other existing approaches of structural analysis, and data visualization within the coronaviral Mpro is also novel and is applicable to other coronaviral proteins.
167. Dissecting Molecular Principles of the Hsp90 Chaperone Regulation by Allosteric Modulators Using a Hierarchical Simulation Approach and Network Modeling of Allosteric Interactions: Conformational Selection Dictates the Diversity of Protein Responses and Ligand-Specific Functional Mechanisms.
     Astl L, Stetz G, Verkhivker GM. J Chem Theory Comput. 2020, 16, 10, 6656-6677. doi: 10.1021/acs.jctc.0c00503.
     Abstract

     Conformational plasticity of the Hsp90 molecular chaperones underlies the diversity of functional mechanisms that these versatile molecular machines employ to coordinate their vast protein clientele in the cellular environment. Despite a steady progress in studies of the Hsp90 machinery, a great deal remains unknown about molecular principles and ligand-specific functional mechanisms of the Hsp90 regulation by allosteric modulators that attracted significant attention because of their therapeutic potential. Due to structural complexity and dynamic nature of the Hsp90 responses to allosteric modulators, the atomistic details about the mode of action of these small molecules continue to be fairly scarce and controversial. In this work, we employ an integrative strategy that encompassed atomistic simulations of the Hsp90 proteins and hierarchical modeling of Hsp90–ligand binding with network analysis to explore functional mechanisms of the Hsp90 regulation by a panel of allosteric modulators (novobiocin, KU-135, KU-174, and KU-32) with different models of action. The results show that functional mechanisms of allosteric modulation in the Hsp90 proteins may be driven by conformational selection principles in which ligands elicit pre-existing states of the unbound chaperone to drive ligand-specific protein responses and distinct scenarios of Hsp90 regulation. We found that novobiocin can selectively sequester an ensemble of open chaperone conformations and inhibit the progression of the functional cycle through a cascade of cumulative dynamic changes. In contrast, KU-32 displayed unique preferences toward partially closed dynamic states, inducing robust allosteric signaling and stimulation of the ATPase cycle. The proposed model of the Hsp90 regulation by allosteric modulators reconciled diverse experimental data and showed that allosteric modulators may operate via targeted exploitation of dynamic landscapes eliciting vastly different protein responses and diverse mechanisms of action.
168. Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning.
     Verkhivker G, Agajanian S, Hu G, Tao P. Front Mol Biosci. 2020, 7, 136. doi: 10.3389/fmolb.2020.00136.
     Abstract

     Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the “second secret of life.” The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
169. Comparative Dynamics and Functional Mechanisms of the CYP17A1 Tunnels Regulated by Ligand Binding.
     Xiao F, Song X, Tian P, Gan M, Verkhivker GM, Hu G. J Chem Inf Model. 2020, 60 7, 3632-3647. doi: 10.1021/acs.jcim.0c00447.
     Abstract

     As an important member of cytochrome P450 (CYP) enzymes, CYP17A1 is a dual-function monooxygenase with a critical role in the synthesis of many human steroid hormones, making it an attractive therapeutic target. The emerging structural information about CYP17A1 and the growing number of inhibitors for these enzymes call for a systematic strategy to delineate and classify mechanisms of ligand transport through tunnels that control catalytic activity. In this work, we applied an integrated computational strategy to different CYP17A1 systems with a panel of ligands to systematically study at the atomic level the mechanism of ligand-binding and tunneling dynamics. Atomistic simulations and binding free energy computations identify the dynamics of dominant tunnels and characterize energetic properties of critical residues responsible for ligand binding. The common transporting pathways including S, 3, and 2c tunnels were identified in CYP17A1 binding systems, while the 2c tunnel is a newly formed pathway upon ligand binding. We employed and integrated several computational approaches including the analysis of functional motions and sequence conservation, atomistic modeling of dynamic residue interaction networks, and perturbation response scanning analysis to dissect ligand tunneling mechanisms. The results revealed the hinge-binding and sliding motions as main functional modes of the tunnel dynamic, and a group of mediating residues as key regulators of tunnel conformational dynamics and allosteric communications. We have also examined and quantified the mutational effects on the tunnel composition, conformational dynamics, and long-range allosteric behavior. The results of this investigation are fully consistent with the experimental data, providing novel rationale to the experiments and offering valuable insights into the relationships between the structure and function of the channel networks and a robust atomistic model of activation mechanisms and allosteric interactions in CYP enzymes.
170. Allosteric Mechanism of the Hsp90 Chaperone Interactions with Cochaperones and Client Proteins by Modulating Communication Spines of Coupled Regulatory Switches: Integrative Atomistic Modeling of Hsp90 Signaling in Dynamic Interaction Networks.
     Astl L, Stetz G, Verkhivker G. J Chem Inf Model. 2020, 60, 7, 3616-3631. doi: 10.1021/acs.jcim.0c00380.
     Abstract

     Conformational landscapes of the Hsp90 chaperones have revealed that the intrinsic plasticity and functional adaptability of these molecular chaperones to a large cohort of cochaperones and a vast protein clientele can be regulated by a number of single switch points broadly dispersed in the chaperone structure. A detailed dynamic view of the allosteric changes mediated by conformational switches and the mechanism of their coupling during the ATPase cycle remains poorly understood and presents an important area of investigation. In this work, we employed integrative computational modeling that included evolutionary and coevolutionary analyses, experiment-guided protein docking and structure modeling, molecular simulations, energetic analysis, and network modeling to perform a systematic characterization of molecular and network signatures of conformational switch points and dissect their allosteric cross-talk in the Hsp90 complexes with cochaperones and client proteins. Using a hierarchical modeling of dynamic interaction networks, we show that the allosteric regulation of the Hsp90 interactions with p23 and Aha1 cochaperones and p53 client protein may be determined by the intramolecular communication “spines” of spatially separated and allosterically coupled regulatory switches. Using a battery of computational approaches, we examined how p23, Aha1, and p53 proteins can modulate signal transmission in the Hsp90 by exploiting communication spines of regulatory switches in the global allosteric network. This study proposes a community-chain mechanism of allosteric coupling between conformational switch centers and identifies key regulatory control points that mediate long-range interactions and communications in the Hsp90 chaperone. The results of this investigation provide novel insights into the nature of allosteric regulation mechanisms in the Hsp90 chaperones and offer a simple mechanistic model of the Hsp90 communications and adaptation to binding partners during the functional cycle.
171. Exploring Mechanisms of Communication Switching in the Hsp90-Cdc37 Regulatory Complexes with Client Kinases through Allosteric Coupling of Phosphorylation Sites: Perturbation-Based Modeling and Hierarchical Community Analysis of Residue Interaction Networks.
     Stetz G, Astl L, Verkhivker GM. J Chem Theory Comput. 2020, 16, 7, 4706-4725. doi: 10.1021/acs.jctc.0c00280.
     Abstract

     Understanding molecular principles underlying chaperone-based modulation of kinase client activity is critically important to dissect functions and activation mechanisms of many oncogenic proteins. The recent experimental studies have suggested that phosphorylation sites in the Hsp90 and Cdc37 proteins can serve as conformational communication switches of chaperone regulation and kinase interactions. However, a mechanism of allosteric coupling between phosphorylation sites in the Hsp90 and Cdc37 during client binding is poorly understood, and the molecular signatures underpinning specific roles of phosphorylation sites in the Hsp90 regulation remain unknown. In this work, we employed a combination of evolutionary analysis, coarse-grained molecular simulations together with perturbation-based network modeling and scanning of the unbound and bound Hsp90 and Cdc37 structures to quantify allosteric effects of phosphorylation sites and identify unique signatures that are characteristic for communication switches of kinase-specific client binding. By using network-based metrics of the dynamic intercommunity bridgeness and community centrality, we characterize specific signatures of phosphorylation switches involved in allosteric regulation. Through perturbation-based analysis of the dynamic residue interaction networks, we show that mutations of kinase-specific phosphorylation switches can induce long-range effects and lead to a global rewiring of the allosteric network and signal transmission in the Hsp90-Cdc37-kinase complex. We determine a specific group of phosphorylation sites in the Hsp90 where mutations may have a strong detrimental effect on allosteric interaction network, providing insight into the mechanism of phosphorylation-induced communication switching. The results demonstrate that kinase-specific phosphorylation switches of communications in the Hsp90 may be partly predisposed for their regulatory role based on preexisting allosteric propensities.
172. Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications.
     Liang Z, Verkhivker G, Hu G. Brief Bioinform. 2020, 21, 3, 815-835. doi: 10.1093/bib/bbz029.
     Abstract

     Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein–DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.
173. Impact of emerging mutations on the dynamic properties the SARS-CoV-2 main protease: an in silico investigation.
     Verkhivker G. J. Chem. Inf. Model. 2020, 60, 10, 5080–5102. doi: 10.1021/acs.jcim.0c00634.
     Abstract

     The new coronavirus (SARS-CoV-2) is a global threat to world health and its economy. Its main protease (Mpro), which functions as a dimer, cleaves viral precursor proteins in the process of viral maturation. It is a good candidate for drug development owing to its conservation and the absence of a human homolog. An improved understanding of the protein behaviour can accelerate the discovery of effective therapies in order to reduce mortality. 100 ns all-atom molecular dynamics simulations of 50 homology modelled mutant Mpro dimers were performed at pH 7 from filtered sequences obtained from the GISAID database. Protease dynamics were analysed using RMSD, RMSF, Rg, the averaged betweenness centrality and geometry calculations. Domains from each Mpro protomer were found to generally have independent motions, while the dimer-stabilising N-finger region was found to be flexible in most mutants. A mirrored interprotomer pocket was found to be correlated to the catalytic site using compaction dynamics, and can be a potential allosteric target. The high number of titratable amino acids of Mpro may indicate an important role of pH on enzyme dynamics, as previously reported for SARS-CoV. Independent coarse-grained Monte Carlo simulations suggest a link between rigidity/mutability and enzymatic function.
174. Dynamic View of Allosteric Regulation in the Hsp70 Chaperones by J-Domain Cochaperone and Post-Translational Modifications: Computational Analysis of Hsp70 Mechanisms by Exploring Conformational Landscapes and Residue Interaction Networks.
     Astl L, Verkhivker G. J Chem Inf Model. 2020, 60, 3, 1614-1631. doi: 10.1021/acs.jcim.9b01045.
     Abstract

     Structural and biochemical studies of Hsp70 chaperones have provided a molecular view of the chaperone biochemical cycle by revealing a complex interplay between allosteric conformational states that controls the feedback loop between stimulation of the adenosinetriphosphatase (ATPase) activity and the substrate release. Allosteric regulation in the Hsp70 chaperones and efficient substrate targeting are mediated by J-domain cochaperones through a dynamic interaction network controlled by the regulatory hotspots. In the current work, we have simulated conformational landscapes and residue interaction networks in the open, closed, and cochaperone-bound DnaK structures. The results of this work have shown that J-domain can selectively enhance direction-specific signal propagation from the substrate-binding domain to the catalytic center and promote the structural environment required for ATP hydrolysis. By employing different network-based approaches, we examined the role and contribution of post-translational modification sites in allosteric regulation of human Hsp70. The central finding of this analysis indicated that conserved phosphorylation sites localized preferentially in the nucleotide-binding domain regions are often aligned with the allosteric control points and serve as effector centers in Hsp70. We have found that cooperation of post-translational modifications sites is based on the governing role of phosphorylation sites in dictating regulatory switching functions, whereas the bulk of acetylation sites can be involved in sensing the long-range signals and executing allosteric changes during the ATPase cycle. The results of this study highlight the important role of phosphorylation sites in exerting control over allosteric changes in Hsp70. The network-centric framework for the analysis of conformational dynamics and chaperone landscapes can explain a range of structural and functional experiments, providing a robust dynamic model of Hsp70 regulation by cochaperones and sites of post-translational modifications.
175. Computational Modeling and Engineering of Allosteric Regulatory Mechanisms in Signaling Proteins: Integration of Multiscale Simulations, Network Biology and Machine Learning.
     Verkhivker G. Biophysical journal. 2020, 118, 3, 206A. doi: https://doi.org/10.1016/j.bpj.2019.11.1238.
     Abstract

     The allosteric interactions and regulation of molecular chaperones and protein kinases allow for molecular communication and event coupling in signal transduction networks. We report the results of integrative systems biology studies of the Hsp90 chaperone and protein kinases with an atomic level analysis of the communication pathways regulating conformational equilibrium of theses protein systems in signaling networks. Biophysical modeling of allosteric regulation in the protein kinases has offered additional insights into organizing principles of kinase activation by molecular chaperones that may be orchestrated by a cross-talk between key regulatory regions. The results of biophysical and computational systems biology analyses combined with proteomics experiments have been integrated into a graph-based network model of allosteric regulation. The evolution of protein structure networks in molecular chaperones and protein kinases during allosteric activation has revealed the increased cooperativity reflecting a preferential attachment of allosterically interacting functional sites. Among our primary findings is the emerging evidence that a small number of functional motifs may be utilized by the chaperone and protein kinases to act collectively as central regulators of the intermolecular communications, ATP hydrolysis, and protein client binding in signaling networks. Integration of computational systems biology and machine learning analysis of the Hsp90 interactions with oncogenic kinase mutants is then used to construct models of allosteric regulation of oncogenic proteins by molecular chaperones in signaling cascades. A computational synthetic biology framework is proposed for design and re-engineering signal transduction networks and pathways that involve cross-talk between molecular chaperones and protein kinase clients. We have also analyzed mechanisms by which kinase drugs and allosteric Hsp90 modulators can act synergistically and exert their pharmacological effect by depriving the client kinase of access to the molecular chaperone.
176. Integrated Computational Approaches and Tools for Allosteric Drug Discovery.
     Sheik Amamuddy O, Veldman W, Manyumwa C, Khairallah A, Agajanian S, Oluyemi O, Verkhivker G, Tastan Bishop O. Int J Mol Sci. 2020, 21, 3, 847. doi: 10.3390/ijms21030847. PMID: 32013012
     Abstract

     Understanding molecular mechanisms underlying the complexity of allosteric regulation in proteins has attracted considerable attention in drug discovery due to the benefits and versatility of allosteric modulators in providing desirable selectivity against protein targets while minimizing toxicity and other side effects. The proliferation of novel computational approaches for predicting ligand–protein interactions and binding using dynamic and network-centric perspectives has led to new insights into allosteric mechanisms and facilitated computer-based discovery of allosteric drugs. Although no absolute method of experimental and in silico allosteric drug/site discovery exists, current methods are still being improved. As such, the critical analysis and integration of established approaches into robust, reproducible, and customizable computational pipelines with experimental feedback could make allosteric drug discovery more efficient and reliable. In this article, we review computational approaches for allosteric drug discovery and discuss how these tools can be utilized to develop consensus workflows for in silico identification of allosteric sites and modulators with some applications to pathogen resistance and precision medicine. The emerging realization that allosteric modulators can exploit distinct regulatory mechanisms and can provide access to targeted modulation of protein activities could open opportunities for probing biological processes and in silico design of drug combinations with improved therapeutic indices and a broad range of activities.

2019

150. Biophysical simulations and structure-based modeling of residue interaction networks in the tumor suppressor proteins reveal functional role of cancer mutation hotspots in molecular communication.
     Verkhivker G. Biochim Biophys Acta Gen Subj. 2019, 1863, 1, 210-225. doi: 10.1016/j.bbagen.2018.10.009.
     Abstract

     In the current study, we have combined molecular simulations and energetic analysis with dynamics-based network modeling and perturbation response scanning to determine molecular signatures of mutational hotspot residues in the p53, PTEN, and SMAD4 tumor suppressor proteins. By examining structure, energetics and dynamics of these proteins, we have shown that inactivating mutations preferentially target a group of structurally stable residues that play a fundamental role in global propagation of dynamic fluctuations and mediating allosteric interaction networks. Through integration of long-range perturbation dynamics and network-based approaches, we have quantified allosteric potential of residues in the studied proteins. The results have revealed that mutational hotspot sites often correspond to high centrality mediating centers of the residue interaction networks that are responsible for coordination of global dynamic changes and allosteric signaling. Our findings have also suggested that structurally stable mutational hotpots can act as major effectors of allosteric interactions and mutations in these positions are typically associated with severe phenotype. Modeling of shortest inter-residue pathways has shown that mutational hotspot sites can also serve as key mediating bridges of allosteric communication in the p53 and PTEN protein structures. Multiple regression models have indicated that functional significance of mutational hotspots can be strongly associated with the network signatures serving as robust predictors of critical regulatory positions responsible for loss-of-function phenotype. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of mutational hotspots, providing a plausible rationale for explaining and localizing disease-causing mutations in tumor suppressor genes.
151. Data-driven computational analysis of allosteric proteins by exploring protein dynamics, residue coevolution and residue interaction networks.
     Astl L, Verkhivker G. Biochim Biophys Acta Gen Subj. 2019, pii: S0304-4165(19)30179-5. doi: 10.1016/j.bbagen.2019.07.008.
     Abstract

     Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks. In this work, we performed a large scale comprehensive and multi-faceted analysis of >300 diverse allosteric proteins and complexes with allosteric modulators. By modeling and exploring coarse-grained dynamics, residue coevolution, and residue interaction networks for allosteric proteins, we have determined unifying molecular signatures shared by allosteric systems. The results of this study have suggested that allosteric inhibitors and allosteric activators may differentially affect global dynamics and network organization of protein systems, leading to diverse allosteric mechanisms. By using structural and functional data on protein kinases, we present a detailed case study that that included atomic-level analysis of coevolutionary networks in kinases bound with allosteric inhibitors and activators.
152. Editorial: Machine Learning in Biomolecular Simulations.
     Verkhivker G, Spiwok V, Gervasio FL. Front Mol Biosci. 2019, 6, 76. doi: 10.3389/fmolb.2019.00076.
153. Establishing Computational Approaches Towards Identifying Malarial Allosteric Modulators: A Case Study of Plasmodium falciparum Hsp70s.
     Amusengeri A, Astl L, Lobb K, Verkhivker G, Tastan Bishop Ö. Int J Mol Sci. 2019, 20, 22, 5574. doi: 10.3390/ijms20225574.
     Abstract

     Combating malaria is almost a never-ending battle, as Plasmodium parasites develop resistance to the drugs used against them, as observed recently in artemisinin-based combination therapies. The main concern now is if the resistant parasite strains spread from Southeast Asia to Africa, the continent hosting most malaria cases. To prevent catastrophic results, we need to find non-conventional approaches. Allosteric drug targeting sites and modulators might be a new hope for malarial treatments. Heat shock proteins (HSPs) are potential malarial drug targets and have complex allosteric control mechanisms. Yet, studies on designing allosteric modulators against them are limited. Here, we identified allosteric modulators (SANC190 and SANC651) against P. falciparum Hsp70-1 and Hsp70-x, affecting the conformational dynamics of the proteins, delicately balanced by the endogenous ligands. Previously, we established a pipeline to identify allosteric sites and modulators. This study also further investigated alternative approaches to speed up the process by comparing all atom molecular dynamics simulations and dynamic residue network analysis with the coarse-grained (CG) versions of the calculations. Betweenness centrality (BC) profiles for PfHsp70-1 and PfHsp70-x derived from CG simulations not only revealed similar trends but also pointed to the same functional regions and specific residues corresponding to BC profile peaks.
154. Integration of Random Forest Classifiers and Deep Convolutional Neural Networks for Classification and Biomolecular Modeling of Cancer Driver Mutations.
     Agajanian S, Oluyemi O, Verkhivker G. Front Mol Biosci. 2019, 6, 44. doi: 10.3389/fmolb.2019.00044.
     Abstract

     Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to preprocess the DNA information. These classifiers were benchmarked against their tree-based alternatives in order to evaluate the performance on a relative scale. We then integrated DNA-based scores generated by CNN with various categories of conservational, evolutionary and functional features into a generalized random forest classifier. The results of this study have demonstrated that CNN can learn high level features from genomic information that are complementary to the ensemble-based predictors often employed for classification of cancer mutations. By combining deep learning-generated score with only two main ensemble-based functional features, we can achieve a superior performance of various machine learning classifiers. Our findings have also suggested that synergy of nucleotide-based deep learning scores and integrated metrics derived from protein sequence conservation scores can allow for robust classification of cancer driver mutations with a limited number of highly informative features. Machine learning predictions are leveraged in molecular simulations, protein stability, and network-based analysis of cancer mutations in the protein kinase genes to obtain insights about molecular signatures of driver mutations and enhance the interpretability of cancer-specific classification models.
155. Interrogating Regulatory Mechanisms in Signaling Proteins by Allosteric Inhibitors and Activators: A Dynamic View through the Lens of Residue Interaction Networks.
     Verkhivker G, Astl L, Tse A. Adv Exp Med Biol. 2019, 1163, 187-223. doi: 10.1007/978-981-13-8719-7_9.
     Abstract

     Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks. In this chapter, we discuss recent developments in understanding of allosteric mechanisms and interactions of protein systems, particularly in the context of structural, functional, and computational studies of allosteric inhibitors and activators. Computational and experimental approaches and advances in understanding allosteric regulatory mechanisms are reviewed to provide a systematic and critical view of the current progress in the development of allosteric modulators and highlight most challenging questions in the field. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Structural and computational studies of protein kinases have generated in recent decade significant insights that allowed leveraging knowledge about conformational diversity and allosteric regulation of protein kinases in the design and discovery of novel kinase drugs. We discuss recent developments in understanding multilayered allosteric regulatory machinery of protein kinases and provide a systematic view of the current state in understanding molecular basis of allostery mediated by kinase inhibitors and activators. In conclusion, we highlight the current status and future prospects of computational biology approaches in bridging the basic science of protein kinases with the discovery of anticancer therapies.
156. Atomistic Modeling of the ABL Kinase Regulation by Allosteric Modulators Using Structural Perturbation Analysis and Community-Based Network Reconstruction of Allosteric Communications.
     Astl L, Verkhivker G. J Chem Theory Comput. 2019, 15, 5, 3362-3380. doi: 10.1021/acs.jctc.9b00119.
     Abstract

     In this work, we have examined the molecular mechanisms of allosteric regulation of the ABL tyrosine kinase at the atomic level. Atomistic modeling of the ABL complexes with a panel of allosteric modulators has been performed using a combination of molecular dynamics simulations, structural residue perturbation scanning, and a novel community analysis of the residue interaction networks. Our results have indicated that allosteric inhibitors and activators may exert a differential control on allosteric signaling between the kinase binding sites and functional regions. While the inhibitor binding can strengthen the closed ABL state and induce allosteric communications directed from the allosteric pocket to the ATP binding site, the DPH activator may induce a more dynamic open form and activate allosteric couplings between the ATP and substrate binding sites. By leveraging a network-centric theoretical framework, we have introduced a novel community analysis method and global topological parameters that have unveiled the hierarchical modularity and the intercommunity bridging sites in the residue interaction network. We have found that allosteric functional hotspots responsible for the kinase regulation may serve the intermodular bridges in the global interaction network. The central conclusion from this analysis is that the regulatory switch centers play a fundamental role in the modular network organization of ABL as the unique intercommunity bridges that connect the SH2 and SH3 domains with the catalytic core into a functional kinase assembly. The hierarchy of network organization in the ABL regulatory complexes may allow for the synergistic action of dense intercommunity links required for the robust signal transfer in the catalytic core and sparse network bridges acting as the regulatory control points that orchestrate allosteric transitions between the inhibited and active kinase forms.
157. Computational Modeling and Engineering of Allosteric Regulatory Mechanisms in Signaling Proteins: Integration of Multiscale Simulations, Network Biology and Machine Learning Book of Abstracts. Albany 2019: The 20th Conversation.
     Verkhivker G. Biophysical Journal. 2020, 118, 3, 206a. doi: 10.1080/07391102.2019.1604468
158. Allosteric mechanism of the circadian protein Vivid resolved through Markov state model and machine learning analysis.
     Zhou H, Dong Z, Verkhivker G, Zoltowski BD, Tao P. PLoS Comput Biol. 2019, 15, 2, e1006801. doi: 10.1371/journal.pcbi.1006801.
     Abstract

     The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms. Applying this new integrative approach, we provided a quantitative evaluation of the contribution from the covalent bond to the protein global conformational change, and proposed an atomistic allosteric mechanism leading to the discovery of the unexpected importance of A’α/Aβ and previously overlooked Eα/Fα loops in the conformational change. This approach could be applicable to other allosteric proteins in general to provide interpretable atomistic representations of their otherwise elusive allosteric mechanisms.

2018

141. Computational modeling of the Hsp90 Interactions with cochaperones and small-molecule inhibitors.
     Verkhivker G. Methods Mol Biol. 2018, 1709, 253-273. doi: 10.1007/978-1-4939-7477-1_19.
     Abstract

     Allosteric interactions of the molecular chaperone Hsp90 with a diverse array of cochaperones and client proteins, such as protein kinases and transcription factors, allow for efficient molecular communication in signal transduction networks. Deregulation of pathways involving these proteins is commonly associated with cancer pathologies and allosteric inhibition of oncogenic clients by targeting Hsp90 provides a powerful therapeutic strategy in cancer research. We review several validated computational approaches and tools used in the studies of the Hsp90 interactions with proteins and small molecules. These methods include experimentally guided docking to predict Hs90-protein interactions, molecular and binding free energy simulations to analyze Hsp90 binding with small molecules, and structure-based network modeling to evaluate allosteric interactions and communications in the Hsp90 regulatory complexes. Through the lens of allosteric-centric view on Hsp90 function and regulation, we discuss newly emerging computational tools that link protein structure modeling with biophysical simulations and network-based systems biology approaches.
142. Dynamics-based community analysis and perturbation response scanning of allosteric interaction networks in the TRAP1 chaperone structures dissect molecular linkage between conformational asymmetry and sequential ATP hydrolysis.
     Verkhivker G. Biochim Biophys Acta Proteins Proteom. 2018, 1866, 8, 899-912. doi: 10.1016/j.bbapap.2018.04.008.
     Abstract

     Allosteric interactions of the Hsp90 chaperones with cochaperones and diverse protein clients can often exhibit distinct asymmetric features that determine regulatory mechanisms and cellular functions in many signaling networks. The recent crystal structures of the mitochondrial Hsp90 isoform TRAP1 in complexes with ATP analogs have provided first evidence of significant asymmetry in the closed dimerized state that triggers independent activity of the chaperone protomers, whereby preferential hydrolysis of the buckled protomer is followed by conformational flipping between protomers and hydrolysis of the second protomer. Despite significant insights in structural characterizations of the TRAP1 chaperone, the atomistic details and mechanics of allosteric interactions that couple sequential ATP hydrolysis with asymmetric conformational switching in the TRAP1 protomers remain largely unknown. In this work, we explored atomistic and coarse-grained simulations of the TRAP1 dimer structures in combination with the ensemble-based network modeling and perturbation response scanning of residue interaction networks to probe salient features underlying allosteric signaling mechanism. This study has revealed that key effector sites that orchestrate allosteric interactions occupy the ATP binding region and N-terminal interface of the buckled protomer, whereas the main sensors of allosteric signals that drive functional conformational changes during ATPase cycle are consolidated near the client binding region of the straight protomer, channeling the energy of ATP hydrolysis for client remodeling. The community decomposition analysis of the interaction networks and reconstruction of allosteric communication pathways in the TRAP1 structures have quantified mechanism of allosteric regulation, revealing control points and interactions that coordinate asymmetric switching during ATP hydrolysis.
143. Multiscale modeling and network-based systems biology analysis of protein kinase regulation by the Hsp90-Cdc37 chaperone system: Towards discovery of synergistic allosteric modulators targeting Hsp90-kinase interactions and evading drug resistance.
     Verkhivker, G. Abstracts of Papers of the American Chemical Society. 2018. WOSUID: WOS:000435537706570
144. Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones.
     Stetz G, Tse A, Verkhivker G. Sci. Rep. 2018,  8, 1, 6899. doi: 10.1038/s41598-018-25329-4.
     Abstract

     Post-translational modifications (PTMs) represent an important regulatory instrument that modulates structure, dynamics and function of proteins. The large number of PTM sites in the Hsp90 proteins that are scattered throughout different domains indicated that synchronization of multiple PTMs through a combinatorial code can be invoked as an important mechanism to orchestrate diverse chaperone functions and recognize multiple client proteins. In this study, we have combined structural and coevolutionary analysis with molecular simulations and perturbation response scanning analysis of the Hsp90 structures to characterize functional role of PTM sites in allosteric regulation. The results reveal a small group of conserved PTMs that act as global mediators of collective dynamics and allosteric communications in the Hsp90 structures, while the majority of flexible PTM sites serve as sensors and carriers of the allosteric structural changes. This study provides a comprehensive structural, dynamic and network analysis of PTM sites across Hsp90 proteins, identifying specific role of regulatory PTM hotspots in the allosteric mechanism of the Hsp90 cycle. We argue that plasticity of a combinatorial PTM code in the Hsp90 may be enacted through allosteric coupling between effector and sensor PTM residues, which would allow for timely response to structural requirements of multiple modified enzymes.
145. Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.
     Agajanian S, Odeyemi O, Bischoff N, Ratra S, Verkhivker G. J Chem Inf Model. 2018, 58, 10, 2131-2150. doi: 10.1021/acs.jcim.8b00414. Epub 2018 Oct 3. PMID: 30253099
     Abstract

     In this study, we developed two cancer-specific machine learning classifiers for prediction of driver mutations in cancer-associated genes that were validated on canonical data sets of functionally validated mutations and applied to a large cancer genomics data set. By examining sequence, structure, and ensemble-based integrated features, we have shown that evolutionary conservation scores play a critical role in classification of cancer drivers and provide the strongest signal in the machine learning prediction. Through extensive comparative analysis with structure–functional experiments and multicenter mutational calling data from Pan Cancer Atlas studies, we have demonstrated the robustness of our models and addressed the validity of computational predictions. To address the interpretability of cancer-specific classification models and obtain novel insights about molecular signatures of driver mutations, we have complemented machine learning predictions with structure–functional analysis of cancer driver mutations in several important oncogenes and tumor suppressor genes. By examining structural and dynamic signatures of known mutational hotspots and the predicted driver mutations, we have shown that the greater flexibility of specific functional regions targeted by driver mutations in oncogenes may facilitate activating conformational changes, while loss-of-function driver mutations in tumor suppressor genes can preferentially target structurally rigid positions that mediate allosteric communications in residue interaction networks and modulate protein binding interfaces. By revealing molecular signatures of cancer driver mutations, our results highlighted limitations of the binary driver/passenger classification, suggesting that functionally relevant cancer mutations may span a continuum spectrum of driverlike effects. Based on this analysis, we propose for experimental testing a group of novel potential driver mutations that can act by altering structure, global dynamics, and allosteric interaction networks in important cancer genes.
146. Functional Role and Hierarchy of the Intermolecular Interactions in Binding of Protein Kinase Clients to the Hsp90-Cdc37 Chaperone: Structure-Based Network Modeling of Allosteric Regulation.
     Stetz G, Verkhivker G. J Chem Inf Model. 2018, 58, 2, 405-421. doi: 10.1021/acs.jcim.7b00638. Epub 2018 Feb 15.
     Abstract

     A fundamental role of the Hsp90–Cdc37 chaperone machinery in mediating conformational development and activation of diverse protein kinase clients is essential for signal transduction. Structural and biochemical studies have demonstrated that characterization of global conformational changes and allosteric interactions in the Hsp90–Cdc37–kinase complexes are central to our understanding of the mechanisms underlying kinase recruitment and processing by the Hsp90–Cdc37 chaperone. The recent cryo-electron microscopy structure of the Hsp90–Cdc37–Cdk4 kinase complex has provided a framework for dissecting regulatory principles underlying differentiation and recruitment of protein kinase clients to the chaperone machinery. In this work, we have characterized functional role and hierarchy of the intermolecular interactions in binding of protein kinase clients to the Hsp90–Cdc37 system. The network analysis revealed important relationships between structural stability, global centrality, and functional significance of regulatory hotspots in chaperone regulation and client recognition. A unique asymmetric topography of the intermolecular communities in the chaperone–kinase complex has quantified a central mediating role of Cdc37 in client recognition and allosteric regulation of the chaperone–kinase complex. Modeling of allosteric pathways in the chaperone complex has further clarified structural and energetic signatures of allosteric hotspots, particularly linking sites of post-translational modifications in Hsp90 with their role in allosteric interactions and client regulation. The results of this integrative computational study are compared with a wide range of structural, biochemical, and cell-based experiments, offering a robust network-centric model of allosteric regulation and client kinase recognition by the Hsp90–Cdc37 chaperone machine.

2017

135. Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication.
     Stetz G, Verkhivker G. PLoS Comput Biol. 2017,13,1,e1005299. doi: 10.1371/journal.pcbi.1005299. DOI: 10.1371/journal.pcbi.1005299
     Abstract

     Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.
136. Design, Synthesis, and Evaluation of Dasatinib-Amino Acid and Dasatinib-Fatty Acid Conjugates as Protein Tyrosine Kinase Inhibitors.
     Tiwari RK, Brown A, Sadeghiani N, Shirazi AN, Bolton J, Tse A, Verkhivker G, Parang K, Sun G. ChemMedChem. 2017,12,1,86-99. doi: 10.1002/cmdc.201600387.
     Abstract

     Derivatives of the tyrosine kinase inhibitor dasatinib were synthesized by esterification with 25 carboxylic acids, including amino acids and fatty acids, thereby extending the drug to interact with more diverse sites and to improve specificity. The dasatinib–l-arginine derivative (Das-R, 7) was found to be the most potent of the inhibitors tested, with IC50 values of 4.4, <0.25, and <0.45 nm against Csk, Src, and Abl kinases, respectively. The highest selectivity ratio obtained in our study, 91.4 Csk/Src, belonged to compound 18 (Das-C10) with an IC50 value of 3.2 μm for Csk compared with 35 nm for Src. Furthermore, many compounds displayed increased selectivity toward Src over Abl. Compounds 15 (Das–glutamic acid) and 13 (Das–cysteine) demonstrated the largest gains (10.2 and 10.3 Abl/Src IC50 ratios). Das-R (IC50=2.06 μm) was significantly more potent than the parent dasatinib (IC50=26.3 μm) against Panc-1 cells, whereas both compounds showed IC50<51.2 pm against BV-173 and K562 cells. Molecular modeling and binding free energy simulations revealed good agreements with the experimental results and rationalized the differences in selectivity among the studied compounds. Integration of experimental and computational approaches in the design and biochemical screening of dasatinib derivatives facilitated rational engineering and diversification of the dasatinib scaffold, providing useful insight into mechanisms of kinase selectivity.
137. Leveraging Structural Diversity and Allosteric Regulatory Mechanisms of Protein Kinases in the Discovery of Small Molecule Inhibitors.
     Verkhivker, G. Current Medicinal Chemistry. 2017, 24, 42, 4838-4872. doi: 10.2174/0929867323666161006113418. doi: 10.2174/0929867323666161006113418
     Abstract

     Protein kinases are versatile molecule switches that govern functional processes in signal transduction networks and regulate fundamental biological processes of cell cycle and organism development. The continuous growth of biological information and a remarkable breath of structural, genetic, and pharmacological studies on protein kinase genes have significantly advanced our knowledge of the kinase activation, drug binding and allosteric mechanisms underlying kinase regulation and interactions in signaling cascades.. Structural and biochemical studies of the genetic and molecular determinants of protein kinases binding with inhibitors have been the cornerstone of drug discovery efforts in clinical oncology leading to proliferation of effective anticancer therapies. Recent advances in understanding allosteric regulation of protein kinases have fueled unprecedented efforts aiming in the discovery of targeted and allosteric kinase inhibitors that can combat cancer mutants and are at the forefront of the precision medicine initiative in oncology. Despite diversity of regulatory scenarios underlying kinase functions, dimerization-driven activation is a common mechanism of allosteric regulation that is shared by many protein kinase families, most notably ErbB and BRAF kinases that play a central role in growth factor signaling and human disease. In this review, we focused on structural, biochemical and computational studies of the ErbB and BRAF kinases and discuss how diversity of the structural landscape for these kinase genes and dimerization- dependent mechanisms of their regulation can be leveraged in the design and discovery of kinase inhibitors and allosteric modulators of kinase activation. The lessons from this analysis could inform discovery of specific targeted therapies and robust drug combinations for cancer treatment.
138. Network-based modelling and percolation analysis of conformational dynamics and activation in the CDK2 and CDK4 proteins: Dynamic and energetic polarization of the kinase lobes may determine divergence of the regulatory mechanisms.
     Verkhivker G. Mol Biosyst. 2017,13,11,2235-2253. doi: 10.1039/c7mb00355b.
     Abstract

     The overarching goal of delineating molecular principles underlying differentiation of the activation mechanisms in cyclin-dependent kinases (CDKs) is important for understanding regulatory divergences among closely related kinases which can be exploited in drug discovery of targeted and allosteric inhibitors. To systematically characterize dynamic, energetic and network signatures of the activation mechanisms, we combined atomistic simulations and elastic network modeling with the analysis of the residue interaction networks and rigidity decomposition of the CDK2-cyclin A and CDK4-cyclin D1/D3 complexes. The results of this study show that divergences in the activation mechanisms of CDK2 and CDK4 may be determined by differences in stabilization and allosteric cooperativity of the regulatory regions. We show that differential stabilization of the kinase lobes in the CDK4-cyclin D complexes caused by the elevated mobility of the N-lobe residues can weaken allosteric interactions between regulatory regions and compromise cooperativity of the inter-lobe motions that is required to trigger activating transitions. Network modelling and percolation analysis were used to emulate thermal unfolding and perform decomposition of rigid and flexible regions in the CDK2 and CDK4 complexes. These simulations showed that the percolation phase transition in the CDK2-cyclin A complexes is highly cooperative and driven by allosteric coupling between functional regions from both kinase lobes. In contrast, the imbalances in the distribution of rigid and flexible regions for the CDK4-cyclin D complexes, which are manifested by the intrinsic instability of the N-lobe, may weaken allosteric interactions and preclude productive activation. The results of this integrative computational study offer a simple and robust network-based model that explains regulatory divergences between CDK2 and CDK4 kinases.
139. Atomistic simulations and network-based modeling of the Hsp90-Cdc37 chaperone binding with Cdk4 client protein: A mechanism of chaperoning kinase clients by exploiting weak spots of intrinsically dynamic kinase domains.
     Czemeres J, Buse K, Verkhivker G. PLoS One. 2017,12,12,e0190267. doi: 10.1371/journal.pone.0190267.
     Abstract

     A fundamental role of the Hsp90 and Cdc37 chaperones in mediating conformational development and activation of diverse protein kinase clients is essential in signal transduction. There has been increasing evidence that the Hsp90-Cdc37 system executes its chaperoning duties by recognizing conformational instability of kinase clients and modulating their folding landscapes. The recent cryo-electron microscopy structure of the Hsp90-Cdc37-Cdk4 kinase complex has provided a framework for dissecting regulatory principles underlying differentiation and recruitment of protein kinase clients to the chaperone machinery. In this work, we have combined atomistic simulations with protein stability and network-based rigidity decomposition analyses to characterize dynamic factors underlying allosteric mechanism of the chaperone-kinase cycle and identify regulatory hotspots that control client recognition. Through comprehensive characterization of conformational dynamics and systematic identification of stabilization centers in the unbound and client- bound Hsp90 forms, we have simulated key stages of the allosteric mechanism, in which Hsp90 binding can induce instability and partial unfolding of Cdk4 client. Conformational landscapes of the Hsp90 and Cdk4 structures suggested that client binding can trigger coordinated dynamic changes and induce global rigidification of the Hsp90 inter-domain regions that is coupled with a concomitant increase in conformational flexibility of the kinase client. This process is allosteric in nature and can involve reciprocal dynamic exchanges that exert global effect on stability of the Hsp90 dimer, while promoting client instability. The network-based rigidity analysis and emulation of thermal unfolding of the Cdk4-cyclin D complex and Hsp90-Cdc37-Cdk4 complex revealed weak spots of kinase instability that are present in the native Cdk4 structure and are targeted by the chaperone during client recruitment. Our findings suggested that this mechanism may be exploited by the Hsp90-Cdc37 chaperone to recruit and protect intrinsically dynamic kinase clients from degradation. The results of this investigation are discussed and interpreted in the context of diverse experimental data, offering new insights into mechanisms of chaperone regulation and binding.
140. Ensemble-based modeling and rigidity decomposition of allosteric interaction networks and communication pathways in cyclin-dependent kinases: Differentiating kinase clients of the Hsp90-Cdc37 chaperone.
     Stetz G, Tse A, Verkhivker G. PLoS One. 2017,12,11,e0186089. doi: 10.1371/journal.pone.0186089.
     Abstract

     The overarching goal of delineating molecular principles underlying differentiation of protein kinase clients and chaperone-based modulation of kinase activity is fundamental to understanding activity of many oncogenic kinases that require chaperoning of Hsp70 and Hsp90 systems to attain a functionally competent active form. Despite structural similarities and common activation mechanisms shared by cyclin-dependent kinase (CDK) proteins, members of this family can exhibit vastly different chaperone preferences. The molecular determinants underlying chaperone dependencies of protein kinases are not fully understood as structurally similar kinases may often elicit distinct regulatory responses to the chaperone. The regulatory divergences observed for members of CDK family are of particular interest as functional diversification among these kinases may be related to variations in chaperone dependencies and can be exploited in drug discovery of personalized therapeutic agents. In this work, we report the results of a computational investigation of several members of CDK family (CDK5, CDK6, CDK9) that represented a broad repertoire of chaperone dependencies—from nonclient CDK5, to weak client CDK6, and strong client CDK9. By using molecular simulations of multiple crystal structures we characterized conformational ensembles and collective dynamics of CDK proteins. We found that the elevated dynamics of CDK9 can trigger imbalances in cooperative collective motions and reduce stability of the active fold, thus creating a cascade of favorable conditions for chaperone intervention. The ensemble-based modeling of residue interaction networks and community analysis determined how differences in modularity of allosteric networks and topography of communication pathways can be linked with the client status of CDK proteins. This analysis unveiled depleted modularity of the allosteric network in CDK9 that alters distribution of communication pathways and leads to impaired signaling in the client kinase. According to our results, these network features may uniquely define chaperone dependencies of CDK clients. The perturbation response scanning and rigidity decomposition approaches identified regulatory hotspots that mediate differences in stability and cooperativity of allosteric interaction networks in the CDK structures. By combining these synergistic approaches, our study revealed dynamic and network signatures that can differentiate kinase clients and rationalize subtle divergences in the activation mechanisms of CDK family members. The therapeutic implications of these results are illustrated by identifying structural hotspots of pathogenic mutations that preferentially target regions of the increased flexibility to enable modulation of activation changes. Our study offers a network-based perspective on dynamic kinase mechanisms and drug design by unravelling relationships between protein kinase dynamics, allosteric communications and chaperone dependencies.

2016

129. Computational studies of allosteric regulation of BRAF kinases: Combining multiscale modeling and network analysis in design of conformation-specific and allosteric modulators targeting oncogenic BRAF mutants.
     Verkhivker G, Blacklock K, Tse A. Abstracts of Papers of the American Chemical Society. 2016. WOSUID: WOS:000431903806559
130. Dissecting allosteric regulatory mechanisms of the Hsp90 chaperone interactions with the protein kinase clients: Integrating structural bioinformatics with multiscale atomistic simulations and biophysical experiments.
     Verkhivker G, Blacklock K, Buchner J. Abstracts of Papers of the American Chemical Society. 2016. WOSUID: WOS:000431903806455.
     Abstract

     Conformational plasticity of the Hsp90 molecular chaperones underlies the diversity of functional mechanisms that these versatile molecular machines employ to coordinate their vast protein clientele in the cellular environment. Despite a steady progress in studies of the Hsp90 machinery, a great deal remains unknown about molecular principles and ligand-specific functional mechanisms of the Hsp90 regulation by allosteric modulators that attracted significant attention because of their therapeutic potential. Due to structural complexity and dynamic nature of the Hsp90 responses to allosteric modulators, the atomistic details about the mode of action of these small molecules continue to be fairly scarce and controversial. In this work, we employ an integrative strategy that encompassed atomistic simulations of the Hsp90 proteins and hierarchical modeling of Hsp90–ligand binding with network analysis to explore functional mechanisms of the Hsp90 regulation by a panel of allosteric modulators (novobiocin, KU-135, KU-174, and KU-32) with different models of action. The results show that functional mechanisms of allosteric modulation in the Hsp90 proteins may be driven by conformational selection principles in which ligands elicit pre-existing states of the unbound chaperone to drive ligand-specific protein responses and distinct scenarios of Hsp90 regulation. We found that novobiocin can selectively sequester an ensemble of open chaperone conformations and inhibit the progression of the functional cycle through a cascade of cumulative dynamic changes. In contrast, KU-32 displayed unique preferences toward partially closed dynamic states, inducing robust allosteric signaling and stimulation of the ATPase cycle. The proposed model of the Hsp90 regulation by allosteric modulators reconciled diverse experimental data and showed that allosteric modulators may operate via targeted exploitation of dynamic landscapes eliciting vastly different protein responses and diverse mechanisms of action.
131. Exploring Molecular Mechanisms of Paradoxical Activation in the BRAF Kinase Dimers: Atomistic Simulations of Conformational Dynamics and Modeling of Allosteric Communication Networks and Signaling Pathways.
     Tse A, Verkhivker G. Plos ONE. 2016,11,11,e0166583. doi: 10.1371/journal.pone.0166583.
     Abstract

     The recent studies have revealed that most BRAF inhibitors can paradoxically induce kinase activation by promoting dimerization and enzyme transactivation. Despite rapidly growing number of structural and functional studies about the BRAF dimer complexes, the molecular basis of paradoxical activation phenomenon is poorly understood and remains largely hypothetical. In this work, we have explored the relationships between inhibitor binding, protein dynamics and allosteric signaling in the BRAF dimers using a network-centric approach. Using this theoretical framework, we have combined molecular dynamics simulations with coevolutionary analysis and modeling of the residue interaction networks to determine molecular determinants of paradoxical activation. We have investigated functional effects produced by paradox inducer inhibitors PLX4720, Dabrafenib, Vemurafenib and a paradox breaker inhibitor PLX7904. Functional dynamics and binding free energy analyses of the BRAF dimer complexes have suggested that negative cooperativity effect and dimer-promoting potential of the inhibitors could be important drivers of paradoxical activation. We have introduced a protein structure network model in which coevolutionary residue dependencies and dynamic maps of residue correlations are integrated in the construction and analysis of the residue interaction networks. The results have shown that coevolutionary residues in the BRAF structures could assemble into independent structural modules and form a global interaction network that may promote dimerization. We have also found that BRAF inhibitors could modulate centrality and communication propensities of global mediating centers in the residue interaction networks. By simulating allosteric communication pathways in the BRAF structures, we have determined that paradox inducer and breaker inhibitors may activate specific signaling routes that correlate with the extent of paradoxical activation. While paradox inducer inhibitors may facilitate a rapid and efficient communication via an optimal single pathway, the paradox breaker may induce a broader ensemble of suboptimal and less efficient communication routes. The central finding of our study is that paradox breaker PLX7904 could mimic structural, dynamic and network features of the inactive BRAF-WT monomer that may be required for evading paradoxical activation. The results of this study rationalize the existing structure-functional experiments by offering a network-centric rationale of the paradoxical activation phenomenon. We argue that BRAF inhibitors that amplify dynamic features of the inactive BRAF-WT monomer and intervene with the allosteric interaction networks may serve as effective paradox breakers in cellular environment.
132. Integrating genetic and structural data on human kinome in network-based modeling of kinase sensitivities and resistance to targeted anticancer drugs.
     Verkhivker, G. Abstracts of Papers of the American Chemical Society. 2016. WOSUID: WOS:000431903806011.
     Abstract

     The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling complex relationships between robustness of targeted kinase genes and binding specificity of targeted kinase drugs. We discuss how these approaches can exploit advances in chemical biology and network science to develop novel strategies for rationally tailored and robust personalized drug therapies.
133. Molecular dynamics simulations and modelling of the residue interaction networks in the BRAF kinase complexes with small molecule inhibitors: probing the allosteric effects of ligand-induced kinase dimerization and paradoxical activation.
     Verkhivker G. Mol Biosyst. 2016,12,10,3146-65. doi: 10.1039/c6mb00298f.
     Abstract

     Protein kinases are central to proper functioning of cellular networks and are an integral part of many signal transduction pathways. The family of protein kinases represents by far the largest and most important class of therapeutic targets in oncology. Dimerization-induced activation has emerged as a common mechanism of allosteric regulation in BRAF kinases, which play an important role in growth factor signalling and human diseases. Recent studies have revealed that most of the BRAF inhibitors can induce dimerization and paradoxically stimulate enzyme transactivation by conferring an active conformation in the second monomer of the kinase dimer. The emerging connections between inhibitor binding and BRAF kinase domain dimerization have suggested a molecular basis of the activation mechanism in which BRAF inhibitors may allosterically modulate the stability of the dimerization interface and affect the organization of residue interaction networks in BRAF kinase dimers. In this work, we integrated structural bioinformatics analysis, molecular dynamics and binding free energy simulations with the protein structure network analysis of the BRAF crystal structures to determine dynamic signatures of BRAF conformations in complexes with different types of inhibitors and probe the mechanisms of the inhibitor-induced dimerization and paradoxical activation. The results of this study highlight previously unexplored relationships between types of BRAF inhibitors, inhibitor-induced changes in the residue interaction networks and allosteric modulation of the kinase activity. This study suggests a mechanism by which BRAF inhibitors could promote or interfere with the paradoxical activation of BRAF kinases, which may be useful in informing discovery efforts to minimize the unanticipated adverse biological consequences of these therapeutic agents.
134. Probing Allosteric Inhibition Mechanisms of the Hsp70 Chaperone Proteins Using Molecular Dynamics Simulations and Analysis of the Residue Interaction Networks.
     Stetz G, Verkhivker G. J Chem Inf Model. 2016,56,8,1490-517. doi: 10.1021/acs.jcim.5b00755.
     Abstract

     Although molecular mechanisms of allosteric regulation in the Hsp70 chaperones have been extensively studied at both structural and functional levels, the current understanding of allosteric inhibition of chaperone activities by small molecules is still lacking. In the current study, using a battery of computational approaches, we probed allosteric inhibition mechanisms of E. coli Hsp70 (DnaK) and human Hsp70 proteins by small molecule inhibitors PET-16 and novolactone. Molecular dynamics simulations and binding free energy analysis were combined with network-based modeling of residue interactions and allosteric communications to systematically characterize and compare molecular signatures of the apo form, substrate-bound, and inhibitor-bound chaperone complexes. The results suggested a mechanism by which the allosteric inhibitors may leverage binding energy hotspots in the interaction networks to stabilize a specific conformational state and impair the interdomain allosteric control. Using the network-based centrality analysis and community detection, we demonstrated that substrate binding may strengthen the connectivity of local interaction communities, leading to a dense interaction network that can promote an efficient allosteric communication. In contrast, binding of PET-16 to DnaK may induce significant dynamic changes and lead to a fractured interaction network and impaired allosteric communications in the DnaK complex. By using a mechanistic-based analysis of distance fluctuation maps and allosteric propensities of protein residues, we determined that the allosteric network in the PET-16 complex may be small and localized due to the reduced communication and low cooperativity of the substrate binding loops, which may promote the higher rates of substrate dissociation and the decreased substrate affinity. In comparison with the significant effect of PET-16, binding of novolactone to HSPA1A may cause only moderate network changes and preserve allosteric coupling between the allosteric pocket and the substrate binding region. The impact of novolactone on the conformational dynamics and allosteric communications in the HSPA1A complex was comparable to the substrate effect, which is consistent with the experimental evidence that PET-16, but not novolactone binding, can significantly decrease substrate affinity. We argue that the unique dynamic and network signatures of PET-16 and novolactone may be linked with the experimentally observed functional effects of these inhibitors on allosteric regulation and substrate binding.
135. INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.
     Verkhivker G. Pac Symp Biocomput. 2016,21,45-56. PubMed PMID: 26776172.
     Abstract

     The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling complex relationships between robustness of targeted kinase genes and binding specificity of targeted kinase drugs. We discuss how these approaches can exploit advances in chemical biology and network science to develop novel strategies for rationally tailored and robust personalized drug therapies.

2015

122. Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins.
     Stetz G, Verkhivker G. PLoS One. 2015,10,11,e0143752. doi: 10.1371/journal.pone.0143752.
     Abstract

     Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations across diverse chaperone functions. This study reconciles a wide spectrum of structural and functional experiments by demonstrating how integration of molecular simulations and network-centric modeling may explain thermodynamic and mechanistic aspects of allosteric regulation in chaperones.
123. Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution.
     Tse A, Verkhivker G. PLoS One. 2015,10,6,e0130203. doi: 10.1371/journal.pone.0130203.
     Abstract

     Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib) and promiscuous (Bosutinib, Dasatinib) kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations of key mediating residues. This study has outlined mechanisms by which inhibitor binding could modulate resilience and efficiency of allosteric interactions in the kinase structures, while preserving structural topology required for catalytic activity and regulation.
124. Molecular Dynamics Simulations and Structural Network Analysis of c-Abl and c-Src Kinase Core Proteins: Capturing Allosteric Mechanisms and Communication Pathways from Residue Centrality.
     Tse A, Verkhivker G. J Chem Inf Model. 2015,55,8,1645-62. doi: 10.1021/acs.jcim.5b00240.
     Abstract

     The Abl and Src tyrosine kinases play a fundamental regulatory role in orchestrating functional processes in cellular networks and represent an important class of therapeutic targets. Crystallographic studies of these kinases have revealed a similar structural organization of multidomain complexes that confers salient features of their regulatory mechanisms. Molecular characterization of the interaction networks and regulatory residues by which the SH3 and SH2 domains act cooperatively with the catalytic domain to suppress or promote kinase activation presents an active area of structural, biochemical, and computational investigations. In this work, we combine biophysical simulations with computational modeling of the residue interaction networks to characterize allosteric mechanisms of kinase regulation and gain insight into differential sensitivity of c-Abl and c-Src kinases to specific drug binding. Using these approaches, we examine dynamics of cooperative rearrangements in the residue interaction networks and elucidate the structural role of regulatory residues responsible for modulation of kinase activity. We have found that global network parameters such as residue centrality can unambiguously distinguish functional sites that are responsible for mediating allosteric interactions in the regulatory assemblies. This study has revealed mechanistic aspects of allosteric mechanisms and communication pathways by which the SH3 and SH2 domains may exert their regulatory influence on the catalytic domain and kinase activity. We have also found that high centrality residues can be linked to each other to form efficient and robust routes that transmit allosteric signals between spatially separated regulatory regions. The presented results have demonstrated that global features of the residue interaction networks may serve as transparent and robust indicators of kinase regulatory mechanisms and accurately pinpoint key functional residues.
125. Small-world networks of residue interactions in the Abl kinase complexes with cancer drugs: topology of allosteric communication pathways can determine drug resistance effects.
     Tse A, Verkhivker G. Mol Biosyst. 2015,11,7,2082-95. doi: 10.1039/c5mb00246j.
     Abstract

     The human protein kinases play a fundamental regulatory role in orchestrating functional processes in complex cellular networks. Understanding how conformational equilibrium between functional kinase states can be modulated by ligand binding or mutations is critical for quantifying molecular basis of allosteric regulation and drug resistance. In this work, molecular dynamics simulations of the Abl kinase complexes with cancer drugs (Imatinib and Dasatinib) were combined with structure-based network modeling to characterize dynamics of the residue interaction networks in these systems. The results have demonstrated that structural architecture of kinase complexes can produce a small-world topology of the interaction networks. Our data have indicated that specific Imatinib binding to a small number of highly connected residues could lead to network-bridging effects and allow for efficient allosteric communication, which is mediated by a dominant pathway sensitive to the unphosphorylated Abl state. In contrast, Dasatinib binding to the active kinase form may activate a broader ensemble of allosteric pathways that are less dependent on the phosphorylation status of Abl and provide a better balance between the efficiency and resilience of signaling routes. Our results have unveiled how differences in the residue interaction networks and allosteric communications of the Abl kinase complexes can be directly related to drug resistance effects. This study offers a plausible perspective on how efficiency and robustness of the residue interaction networks and allosteric pathways in kinase structures may be associated with protein responses to drug binding.

2014

118. Allosteric Regulation of the Hsp90 Dynamics and Stability by Client Recruiter Cochaperones: Protein Structure Network Modeling.
     Blacklock K, Verkhivker G. PLoS One. 2014,9,1,e86547. doi: 10.1371/journal.pone.0086547.
     Abstract

     The fundamental role of the Hsp90 chaperone in supporting functional activity of diverse protein clients is anchored by specific cochaperones. A family of immune sensing client proteins is delivered to the Hsp90 system with the aid of cochaperones Sgt1 and Rar1 that act cooperatively with Hsp90 to form allosterically regulated dynamic complexes. In this work, functional dynamics and protein structure network modeling are combined to dissect molecular mechanisms of Hsp90 regulation by the client recruiter cochaperones. Dynamic signatures of the Hsp90-cochaperone complexes are manifested in differential modulation of the conformational mobility in the Hsp90 lid motif. Consistent with the experiments, we have determined that targeted reorganization of the lid dynamics is a unifying characteristic of the client recruiter cochaperones. Protein network analysis of the essential conformational space of the Hsp90-cochaperone motions has identified structurally stable interaction communities, interfacial hubs and key mediating residues of allosteric communication pathways that act concertedly with the shifts in conformational equilibrium. The results have shown that client recruiter cochaperones can orchestrate global changes in the dynamics and stability of the interaction networks that could enhance the ATPase activity and assist in the client recruitment. The network analysis has recapitulated a broad range of structural and mutagenesis experiments, particularly clarifying the elusive role of Rar1 as a regulator of the Hsp90 interactions and a stability enhancer of the Hsp90-cochaperone complexes. Small-world organization of the interaction networks in the Hsp90 regulatory complexes gives rise to a strong correspondence between highly connected local interfacial hubs, global mediator residues of allosteric interactions and key functional hot spots of the Hsp90 activity. We have found that cochaperone-induced conformational changes in Hsp90 may be determined by specific interaction networks that can inhibit or promote progression of the ATPase cycle and thus control the recruitment of client proteins.
119. Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications.
     Blacklock K, Verkhivker G. PLoS Comput Biol. 2014,10,6,e1003679. doi: 10.1371/journal.pcbi.1003679.
     Abstract

     A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.
120. Computational Studies of Allosteric Regulation in the Hsp90 Molecular Chaperone: From Functional Dynamics and Protein Structure Networks to Allosteric Communications and Targeted Anti-Cancer Modulators.
     Verkhivker G. Israel Journal of Chemistry. 2014, 54, 8-9,1052-1064. doi: 10.1002/ijch.201300143.
     Abstract

     Computational studies of allosteric interactions have witnessed a recent renaissance fueled by growing inter- est in the modeling of complex molecular assemblies and biological networks. Allosteric interactions of the molecular chaperone Hsp90 with a diverse array of cochaperones and client proteins allow for molecular communication in signal transduction networks. In this review, recent developments in the understanding of allosteric interactions in the context of structural, functional, and computational studies of the Hsp90 chaperone are discussed. A comprehensive analysis of structural and network-based models of protein allostery is provided. Computational and experimental approaches and advances in the understanding of Hsp90 interactions and regulatory mechanisms are reviewed to provide a sys- tematic and critical view of the current progress and most challenging questions in the field. The current status and future prospects for translational research, bridging the basic science of chaperones with the discovery of anti- cancer therapies, are also highlighted.
121. Structure-based network analysis of activation mechanisms in the ErbB family of receptor tyrosine kinases: the regulatory spine residues are global mediators of structural stability and allosteric interactions.
     James KA, Verkhivker G. PLoS One. 2014,9,11,3113488. doi:10.1371/journal.pone.0113488.
     Abstract

     A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.
122. Structure-functional prediction and analysis of cancer mutation effects in protein kinases.
     Dixit A, Verkhivker G. Comput Math Methods Med 2014. 2014, 653487. doi: 10.1155/2014/653487.
     Abstract

     A central goal of cancer research is to discover and characterize the functional effects of mutated genes that contribute to tumorigenesis. In this study, we provide a detailed structural classification and analysis of functional dynamics for members of protein kinase families that are known to harbor cancer mutations. We also present a systematic computational analysis that combines sequence and structure-based prediction models to characterize the effect of cancer mutations in protein kinases. We focus on the differential effects of activating point mutations that increase protein kinase activity and kinase-inactivating mutations that decrease activity. Mapping of cancer mutations onto the conformational mobility profiles of known crystal structures demonstrated that activating mutations could reduce a steric barrier for the movement from the basal “low” activity state to the “active” state. According to our analysis, the mechanism of activating mutations reflects a combined effect of partial destabilization of the kinase in its inactive state and a concomitant stabilization of its active-like form, which is likely to drive tumorigenesis at some level. Ultimately, the analysis of the evolutionary and structural features of the major cancer-causing mutational hotspot in kinases can also aid in the correlation of kinase mutation effects with clinical outcomes.

2013

113. Differential modulation of functional dynamics and allosteric interactions in the Hsp90-cochaperone complexes with p23 and Aha1: a computational study.
     Blacklock K, Verkhivker G. PLoS One. 2013, 8,8,e71936. doi: 10.1371/journal.pone.0071936.
     Abstract

     Allosteric interactions of the molecular chaperone Hsp90 with a large cohort of cochaperones and client proteins allow for molecular communication and event coupling in signal transduction networks. The integration of cochaperones into the Hsp90 system is driven by the regulatory mechanisms that modulate the progression of the ATPase cycle and control the recruitment of the Hsp90 clientele. In this work, we report the results of computational modeling of allosteric regulation in the Hsp90 complexes with the cochaperones p23 and Aha1. By integrating protein docking, biophysical simulations, modeling of allosteric communications, protein structure network analysis and the energy landscape theory we have investigated dynamics and stability of the Hsp90-p23 and Hsp90-Aha1 interactions in direct comparison with the extensive body of structural and functional experiments. The results have revealed that functional dynamics and allosteric interactions of Hsp90 can be selectively modulated by these cochaperones via specific targeting of the regulatory hinge regions that could restrict collective motions and stabilize specific chaperone conformations. The protein structure network parameters have quantified the effects of cochaperones on conformational stability of the Hsp90 complexes and identified dynamically stable communities of residues that can contribute to the strengthening of allosteric interactions. According to our results, p23-mediated changes in the Hsp90 interactions may provide “molecular brakes” that could slow down an efficient transmission of the inter-domain allosteric signals, consistent with the functional role of p23 in partially inhibiting the ATPase cycle. Unlike p23, Aha1-mediated acceleration of the Hsp90-ATPase cycle may be achieved via modulation of the equilibrium motions that facilitate allosteric changes favoring a closed dimerized form of Hsp90. The results of our study have shown that Aha1 and p23 can modulate the Hsp90-ATPase activity and direct the chaperone cycle by exerting the precise control over structural stability, global movements and allosteric communications in Hsp90.
114. Experimentally guided structural modeling and dynamics analysis of Hsp90-p53 interactions: allosteric regulation of the Hsp90 chaperone by a client protein.
     Blacklock K, Verkhivker G. J Chem Inf Model. 2013, 53,11,2962-78. doi: 10.1021/ci400434g.
     Abstract

       A fundamental role of the Hsp90 chaperone system in mediating maturation of protein clients is essential for the integrity of signaling pathways involved in cell cycle control and organism development. Molecular characterization of Hsp90 interactions with client proteins is fundamental to understanding the activity of many tumor-inducing signaling proteins and presents an active area of structural and biochemical studies. In this work, we have probed mechanistic aspects of allosteric regulation of Hsp90 by client proteins via a detailed computational study of Hsp90 interactions with the tumor suppressor protein p53. Experimentally guided protein docking and molecular dynamics structural refinement have reconstructed the recognition-competent states of the Hsp90-p53 complexes that are consistent with the NMR studies. Protein structure network analysis has identified critical interacting networks and specific residues responsible for structural integrity and stability of the Hsp90-p53 complexes. Coarse-grained modeling was used to characterize the global dynamics of the regulatory complexes and map p53-induced changes in the conformational equilibrium of Hsp90. The variations in the functional dynamics profiles of the Hsp90-p53 complexes are consistent with the NMR studies and could explain differences in the functional role of the alternative binding sites. Despite the overall similarity of the collective movements and the same global interaction footprint, p53 binding at the C-terminal interaction site of Hsp90 may have a more significant impact on the chaperone dynamics, which is consistent with the stronger allosteric effect of these interactions revealed by the experimental studies. The results suggest that p53-induced modulation of the global dynamics and structurally stable interaction networks can target the regulatory hinge regions and facilitate stabilization of the closed Hsp90 dimer that underlies the fundamental stimulatory effect of the p53 client.
115. Structural bioinformatics and protein docking analysis of the molecular chaperone-kinase interactions: towards allosteric inhibition of protein kinases by targeting the hsp90-cdc37 chaperone machinery.
     Lawless N, Blacklock K, Berrigan E, Verkhivker G. Pharmaceuticals (Basel). 2013, 6,11,1407-28. doi: 10.3390/ph6111407.
     Abstract

     A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4) kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional “molecular brakes” that can lock (or unlock) kinase from the system during client loading (release) stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

2012

110. From coding variant to structure and function insight.
     Friedman A.J, Torkamani A, Verkhivker G, Schork N.J. Proteomics Research Journal. 2012. EID: 2-s2.0-84892461701
111. Integrating ligand-based and protein-centric virtual screening of kinase inhibitors using ensembles of multiple protein kinase genes and conformations.
     Dixit A, Verkhivker G. J Chem Inf Model. 2012, 52,10,2501-15. doi: 10.1021/ci3002638.
     Abstract

     : The rapidly growing wealth of structural and functional information about kinase genes and kinase inhibitors that is fueled by a significant therapeutic role of this protein family provides a significant impetus for development of targeted computational screening approaches. In this work, we explore an ensemble-based, protein-centric approach that allows for simultaneous virtual ligand screening against multiple kinase genes and multiple kinase receptor conformations. We systematically analyze and compare the results of ligand-based and protein-centric screening approaches using both single-receptor and ensemble-based docking protocols. A panel of protein kinase targets that includes ABL, EGFR, P38, CDK2, TK, and VEGFR2 kinases is used in this comparative analysis. By applying various performance metrics we have shown that ligand-centric shape matching can provide an effective enrichment of active compounds outperforming single-receptor docking screening. However, ligand-based approaches can be highly sensitive to the choice of inhibitor queries. Employment of multiple inhibitor queries combined with parallel selection ranking criteria can improve the performance and efficiency of ligand-based virtual screening. We also demonstrated that replica-exchange Monte Carlo docking with kinome-based ensembles of multiple crystal structures can provide a superior early enrichment on the kinase targets. The central finding of this study is that incorporation of the template-based structural information about kinase inhibitors and protein kinase structures in diverse functional states can significantly enhance the overall performance and robustness of both ligand and protein-centric screening strategies. The results of this study may be useful in virtual screening of kinase inhibitors potentially offering a beneficial spectrum of therapeutic activities across multiple disease states.
112. Probing molecular mechanisms of the hsp90 chaperone: biophysical modeling identifies key regulators of functional dynamics.
     Dixit A, Verkhivker G. PLoS One. 2012, 7,5,e37605. doi: 10.1371/journal.pone.0037605.
     Abstract

     Deciphering functional mechanisms of the Hsp90 chaperone machinery is an important objective in cancer biology aiming to facilitate discovery of targeted anti-cancer therapies. Despite significant advances in understanding structure and function of molecular chaperones, organizing molecular principles that control the relationship between conformational diversity and functional mechanisms of the Hsp90 activity lack a sufficient quantitative characterization. We combined molecular dynamics simulations, principal component analysis, the energy landscape model and structure-functional analysis of Hsp90 regulatory interactions to systematically investigate functional dynamics of the molecular chaperone. This approach has identified a network of conserved regions common to the Hsp90 chaperones that could play a universal role in coordinating functional dynamics, principal collective motions and allosteric signaling of Hsp90. We have found that these functional motifs may be utilized by the molecular chaperone machinery to act collectively as central regulators of Hsp90 dynamics and activity, including the inter-domain communications, control of ATP hydrolysis, and protein client binding. These findings have provided support to a long-standing assertion that allosteric regulation and catalysis may have emerged via common evolutionary routes. The interaction networks regulating functional motions of Hsp90 may be determined by the inherent structural architecture of the molecular chaperone. At the same time, the thermodynamics- based ‘‘conformational selection’’ of functional states is likely to be activated based on the nature of the binding partner. This mechanistic model of Hsp90 dynamics and function is consistent with the notion that allosteric networks orchestrating cooperative protein motions can be formed by evolutionary conserved and sparsely connected residue clusters. Hence, allosteric signaling through a small network of distantly connected residue clusters may be a rather general functional requirement encoded across molecular chaperones. The obtained insights may be useful in guiding discovery of allosteric Hsp90 inhibitors targeting protein interfaces with co-chaperones and protein binding clients.
113. Simulating Molecular Mechanisms of the MDM2-Mediated Regulatory Interactions: A Conformational Selection Model of the MDM2 Lid Dynamics.
     Verkhivker G. Plos One. 2012, 7,7,e40897. doi: 10.1371/journal.pone.0040897.
     Abstract

       Diversity and complexity of MDM2 mechanisms govern its principal function as the cellular antagonist of the p53 tumor suppressor. Structural and biophysical studies have demonstrated that MDM2 binding could be regulated by the dynamics of a pseudo-substrate lid motif. However, these experiments and subsequent computational studies have produced conflicting mechanistic models of MDM2 function and dynamics. We propose a unifying conformational selection model that can reconcile experimental findings and reveal a fundamental role of the lid as a dynamic regulator of MDM2-mediated binding. In this work, structure, dynamics and energetics of apo-MDM2 are studied as a function of posttranslational modifications and length of the lid. We found that the dynamic equilibrium between ‘‘closed’’ and ‘‘semi-closed’’ lid forms may be a fundamental characteristic of MDM2 regulatory interactions, which can be modulated by phosphorylation, phosphomimetic mutation as well as by the lid size. Our results revealed that these factors may regulate p53-MDM2 binding by fine-tuning the thermodynamic equilibrium between preexisting conformational states of apo-MDM2. In agreement with NMR studies, the effect of phosphorylation on MDM2 interactions was more pronounced with the truncated lid variant that favored the thermodynamically dominant closed form. The phosphomimetic mutation S17D may alter the lid dynamics by shifting the thermodynamic equilibrium towards the ensemble of ‘‘semi-closed’’ conformations. The dominant ‘‘semi- closed’’ lid form and weakened dependence on the phosphorylation seen in simulations with the complete lid can provide a rationale for binding of small p53-based mimetics and inhibitors without a direct competition with the lid dynamics. The results suggested that a conformational selection model of preexisting MDM2 states may provide a robust theoretical framework for understanding MDM2 dynamics. Probing biological functions and mechanisms of MDM2 regulation would require further integration of computational and experimental studies and may help to guide drug design of novel anti- cancer therapeutics.

2011

106. A systematic protocol for the characterization of Hsp90 modulators.
     Matts RL, Brandt GEL, Lu Y, Dixit A, Mollapour M, Wang S, Donnelly AC, Neckers L, Verkhivker GM, Blagg BSJ. Bioorg Med Chem. 2011, 19,1,684-92. doi: 10.1016/j.bmc.2010.10.029.
     Abstract

     Several Hsp90 modulators have been identified including the N-terminal ligand geldanamycin (GDA), the C-terminal ligand novobiocin (NB), and the co-chaperone disruptor celastrol. Other Hsp90 modulators elicit a mechanism of action that remains unknown. For example, the natural product gedunin and the synthetic anti-spermatogenic agent H2-gamendazole, recently identified Hsp90 modulators, manifest biological activity through undefined mechanisms. Herein, we report a series of biochemical techniques used to classify such modulators into identifiable categories. Such studies provided evidence that gedunin and H2-gamendazole both modulate Hsp90 via a mechanism similar to celastrol, and unlike NB or GDA.
107. Computational modeling of allosteric communication reveals organizing principles of mutation-induced signaling in ABL and EGFR kinases.
     Dixit A, Verkhivker G. PLoS Comput Biol. 2011, 7,10,e1002179. doi: 10.1371/journal.pcbi.1002179.
     Abstract

     The emerging structural information about allosteric kinase complexes and the growing number of allosteric inhibitors call for a systematic strategy to delineate and classify mechanisms of allosteric regulation and long-range communication that control kinase activity. In this work, we have investigated mechanistic aspects of long-range communications in ABL and EGFR kinases based on the results of multiscale simulations of regulatory complexes and computational modeling of signal propagation in proteins. These approaches have been systematically employed to elucidate organizing molecular principles of allosteric signaling in the ABL and EGFR multi-domain regulatory complexes and analyze allosteric signatures of the gate-keeper cancer mutations. We have presented evidence that mechanisms of allosteric activation may have universally evolved in the ABL and EGFR regulatory complexes as a product of a functional cross-talk between the organizing αF-helix and conformationally adaptive αI-helix and αC-helix. These structural elements form a dynamic network of efficiently communicated clusters that may control the long-range interdomain coupling and allosteric activation. The results of this study have unveiled a unifying effect of the gate-keeper cancer mutations as catalysts of kinase activation, leading to the enhanced long-range communication among allosterically coupled segments and stabilization of the active kinase form. The results of this study can reconcile recent experimental studies of allosteric inhibition and long-range cooperativity between binding sites in protein kinases. The presented study offers a novel molecular insight into mechanistic aspects of allosteric kinase signaling and provides a quantitative picture of activation mechanisms in protein kinases at the atomic level.
108. Elucidation and assessment of the Hsp90 C-terminal inhibitor binding site.
     Matts RL, Dixit A, Peterson LB, Sun L, Voruganti S, Kalyanaraman, Hartson SD, Verkhivker GM, Blagg BSJ. ACS Chem Biol. 2011, 6,8,800-807. doi: 10.1021/cb200052x.
     Abstract

     The Hsp90 chaperone machine is required for the folding, activation, and/or stabilization of more than 50 proteins directly related to malignant progression. Hsp90 contains small molecule binding sites at both its N- and C-terminal domains; however, limited structural and biochemical data regarding the C-terminal binding site is available. In this report, the small molecule binding site in the Hsp90 C-terminal domain was revealed by protease fingerprinting and photoaffinity labeling utilizing LC-MS/MS. The identified site was characterized by generation of a homology model for hHsp90α using the SAXS open structure of HtpG and docking the bioactive conformation of NB into the generated model. The resulting model for the bioactive conformation of NB bound to Hsp90α is presented herein.
109. The energy landscape analysis of cancer mutations in protein kinases.
     Dixit A, Verkhivker GM. PLoS One. 2011, 6,10,e26071. doi: 10.1371/journal.pcbi.1002179.
     Abstract

       The growing interest in quantifying the molecular basis of protein kinase activation and allosteric regulation by cancer mutations has fueled computational studies of allosteric signaling in protein kinases. In the present study, we combined computer simulations and the energy landscape analysis of protein kinases to characterize the interplay between oncogenic mutations and locally frustrated sites as important catalysts of allostetric kinase activation. While structurally rigid kinase core constitutes a minimally frustrated hub of the catalytic domain, locally frustrated residue clusters, whose interaction networks are not energetically optimized, are prone to dynamic modulation and could enable allosteric conformational transitions. The results of this study have shown that the energy landscape effect of oncogenic mutations may be allosteric eliciting global changes in the spatial distribution of highly frustrated residues. We have found that mutation-induced allosteric signaling may involve a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. The presented study has demonstrated that activation cancer mutations may affect the thermodynamic equilibrium between kinase states by allosterically altering the distribution of locally frustrated sites and increasing the local frustration in the inactive form, while eliminating locally frustrated sites and restoring structural rigidity of the active form. The energy landsape analysis of protein kinases and the proposed role of locally frustrated sites in activation mechanisms may have useful implications for bioinformatics-based screening and detection of functional sites critical for allosteric regulation in complex biomolecular systems.
110. Computational Modeling of Allosteric Communication Reveals Organizing Principles of Mutation-Induced Signaling in ABL and EGFR Kinases.
     Dixit A, Verkhivker GM. PLoS Comput Biol. 2011, 7,10,e1002179. doi: 10.1371/journal.pcbi.1002179.
     Abstract

     The emerging structural information about allosteric kinase complexes and the growing number of allosteric inhibitors call for a systematic strategy to delineate and classify mechanisms of allosteric regulation and long-range communication that control kinase activity. In this work, we have investigated mechanistic aspects of long-range communications in ABL and EGFR kinases based on the results of multiscale simulations of regulatory complexes and computational modeling of signal propagation in proteins. These approaches have been systematically employed to elucidate organizing molecular principles of allosteric signaling in the ABL and EGFR multi-domain regulatory complexes and analyze allosteric signatures of the gate- keeper cancer mutations. We have presented evidence that mechanisms of allosteric activation may have universally evolved in the ABL and EGFR regulatory complexes as a product of a functional cross-talk between the organizing aF-helix and conformationally adaptive aI-helix and aC-helix. These structural elements form a dynamic network of efficiently communicated clusters that may control the long-range interdomain coupling and allosteric activation. The results of this study have unveiled a unifying effect of the gate-keeper cancer mutations as catalysts of kinase activation, leading to the enhanced long-range communication among allosterically coupled segments and stabilization of the active kinase form. The results of this study can reconcile recent experimental studies of allosteric inhibition and long-range cooperativity between binding sites in protein kinases. The presented study offers a novel molecular insight into mechanistic aspects of allosteric kinase signaling and provides a quantitative picture of activation mechanisms in protein kinases at the atomic level.
111. Elucidation of the Hsp90 C-terminal inhibitor binding site.
     Matts RL, Dixit A, Peterson LB, Sun L, Voruganti S, Kalyanaraman P, Hartson SD, Verkhivker G, Blagg BS. ACS Chem Biol. 2011 Aug 19;6(8):800-7. doi: 10.1021/cb200052x.
     Abstract

     The Hsp90 chaperone machine is required for the folding, activation, and/or stabilization of more than 50 proteins directly related to malignant progression. Hsp90 contains small molecule binding sites at both its N- and C-terminal domains; however, limited structural and biochemical data regarding the C-terminal binding site is available. In this report, the small molecule binding site in the Hsp90 C-terminal domain was revealed by protease fingerprinting and photoaffinity labeling utilizing LC-MS/MS. The identified site was characterized by generation of a homology model for hHsp90α using the SAXS open structure of HtpG and docking the bioactive conformation of NB into the generated model. The resulting model for the bioactive conformation of NB bound to Hsp90α is presented herein.
112. From coding variants to structure and function insights.
     Friedman A, Torkamani A, Verkhivker GM, Schork NJ. In the book “Protein Structure” Ed.Lauren M. Haggerty Series: Protein Science and Engineering Nova Science Publishers, 2011, 3:395-405.
     Abstract

     The availability of cost-effective DNA sequencing technologies has led to the identification and cataloguing of millions of naturally occurring inherited and somatic human genomic variations. As a result, questions concerning the ultimate phenotypic and functional significance of these variations have been raised. Although some large-scale initiatives have been launched for this purpose, including the Encyclopedia of DNA Elements (ENCODE) initiative, there is a need for the DNA sequencing and genomics communities to reach out and foster greater collaborative opportunities with the functional genomics community. One area that is ripe for this kind of activity is the functional characterization of coding variations, as structural proteomics and crystallography researchers may both benefit from, and contribute to, an understanding of the molecular and phenotypic influence of such variations. We briefly review the motivation for this kind of interaction and draw on publicly available data to showcase its need. We also consider how relevant research could be pursued.
113. The Energy Landscape Analysis of Cancer Mutations in Protein Kinases
     Dixit A, Verkhivker, G. PLoS One. 2011, 6,10,e26071. doi: 10.1371/journal.pone.0026071.
     Abstract

     The growing interest in quantifying the molecular basis of protein kinase activation and allosteric regulation by cancer mutations has fueled computational studies of allosteric signaling in protein kinases. In the present study, we combined computer simulations and the energy landscape analysis of protein kinases to characterize the interplay between oncogenic mutations and locally frustrated sites as important catalysts of allostetric kinase activation. While structurally rigid kinase core constitutes a minimally frustrated hub of the catalytic domain, locally frustrated residue clusters, whose interaction networks are not energetically optimized, are prone to dynamic modulation and could enable allosteric conformational transitions. The results of this study have shown that the energy landscape effect of oncogenic mutations may be allosteric eliciting global changes in the spatial distribution of highly frustrated residues. We have found that mutation-induced allosteric signaling may involve a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. The presented study has demonstrated that activation cancer mutations may affect the thermodynamic equilibrium between kinase states by allosterically altering the distribution of locally frustrated sites and increasing the local frustration in the inactive form, while eliminating locally frustrated sites and restoring structural rigidity of the active form. The energy landsape analysis of protein kinases and the proposed role of locally frustrated sites in activation mechanisms may have useful implications for bioinformatics-based screening and detection of functional sites critical for allosteric regulation in complex biomolecular systems.

2010

98. Dynamics-Based Discovery of Allosteric Inhibitors: Selection of New Ligands for the C-terminal Domain of Hsp90.
    Morra G, Neves MAC, Plescia CJ, Tsustsumi C, Neckers L, Verkhivker GM, Altieri DC, Colombo G. J Chem Theory Comput. 2010, 6,9,2978-89. doi: 10.1021/ct100334n.
    Abstract

      The study of allosteric functional modulation in dynamic proteins is attracting increasing attention. In particular, the discovery of new allosteric sites may generate novel opportunities and strategies for drug development, overcoming the limits of classical active-site oriented drug design. In this paper, we report on the results of a novel, ab initio, fully computational approach for the discovery of allosteric inhibitors based on the physical characterization of signal propagation mechanisms in proteins and apply it to the important molecular chaperone Hsp90. We first characterize the allosteric “hot spots” involved in interdomain communication pathways from the nucleotide-binding site in the N-domain to the distal C-domain. On this basis, we develop dynamic pharmacophore models to screen drug libraries in the search for small molecules with the functional and conformational properties necessary to bind these “hot spot” allosteric sites. Experimental tests show that the selected moelcules bind the Hsp90 C-domain, exhibit antiproliferative activity in different tumor cell lines, while not affecting proliferation of normal human cells, destabilize Hsp90 client proteins, and disrupt association with several cochaperones known to bind the N- and M-domains of Hsp90. These results prove that the hits alter Hsp90 function by affecting its conformational dynamics and recognition properties through an allosteric mechanism. These findings provide us with new insights on the discovery and development of new allosteric inhibitors that are active on important cellular pathways through computational biology. Though based on the specific case of Hsp90, our approach is general and can readily be extended to other target proteins and pathways.

2009

97. Cancer driver mutations in protein kinase genes.
    Torkamani A, Verkhivker G,  Schork N. J. Cancer Lett. 2009, 281,2,117-27. doi: 10.1016/j.canlet.2008.11.008.
    Abstract

    Recent studies investigating the genetic determinants of cancer suggest that some of the genetic alterations contributing to tumorigenesis may be inherited, but the vast majority is somatically acquired during the transition of a normal cell to a cancer cell. A systematic understanding of the genetic and molecular determinants of cancers has already begun to have a transformative effect on the study and treatment of cancer, particularly through the identification of a range of genetic alterations in protein kinase genes, which are highly associated with the disease. Since kinases are prominent therapeutic targets for intervention within the cancer cell, studying the impact that genomic alterations within them have on cancer initiation, progression, and treatment is both logical and timely. In fact, recent sequencing and resequencing (i.e., polymorphism identification) efforts have catalyzed the quest for protein kinase ‘driver’ mutations (i.e., those genetic alterations which contribute to the transformation of a normal cell to a proliferating cancerous cell) in distinction to kinase ‘passenger’ mutations which reflect mutations that merely build up in course of normal and unchecked (i.e., cancerous) somatic cell replication and proliferation. In this review, we discuss the recent progress in the discovery and functional characterization of protein kinase cancer driver mutations and the implications of this progress for understanding tumorigenesis as well as the design of ‘personalized’ cancer therapeutics that target an individual’s unique mutational profile.
98. Characterization of Multiple Stable Conformers of the EC5 Domain of E-cadherin and the Interaction of EC5 with E-cadherin Peptides.
    Zheng K, Laurence J. S, Kuczera K, Verkhivker G, Middaugh C. R, Siahaan T. J. Chem Biol Drug Des. 2009, 73,6,584-98. doi: 10.1111/j.1747-0285.2009.00818.x.
    Abstract

    The objectives of this work were to express the EC5 domain of E-cadherin and determine its structural characteristics as well as to evaluate the binding properties of HAV and BLG4 peptides to EC5 using spectroscopic methods. Homophilic interactions of E-cadherins are responsible for cell-cell adhesion in the adherens junctions of the biological barriers (i.e. intestinal mucosa and blood-brain barriers). The EC5 domain of E-cadherin has an important role in T-cell adhesion to intestinal mucosa via alpha(E)beta(7) integrin-E-cadherin interactions. In this study, the expressed EC5 has a high thermal stability (T(m) = 64.3 degrees C); it also has two stable conformations at room temperature, which convert to one conformation at approximately 54.5 degrees C. NMR and FTIR showed that HAV and BLG4 peptides bind to EC5. HSQC-NMR showed that either Asn or Gln of EC5 was involved in the interactions with HAV and BLG4 peptides. EC5 underwent a conformational change upon interaction with the HAV and BLG4 peptides. Finally, the binding properties of both peptides were modeled by docking experiments, and the results suggest that Asn-46 and Asn-75 of EC5 could be involved during the interaction with the peptides and that the Ser and Trp residues of the HAV and BLG4 peptides, respectively, were important for binding to EC5.
99. Coarse-Grained Modeling of the HIV-1 Protease Binding Mechanisms: I. Targeting Structural Flexibility of the Protease Flaps and Implications for Drug Design.
    Verkhivker G. Computational Intelligence Methods for Bioinformatics and Biostatistics. 2009. WOSUID: WOS:000268882700001
    Abstract

    We propose a coarse–grained model to study binding mechanism of the HIV–1 protease inhibitors using long equilibrium simulations with an ensemble of the HIV–1 protease crystal structures. A microscopic analysis suggests a binding mechanism, in which the HIV–1 protease drugs may exploit the dynamic equilibrium between thermodynamically stable, high affinity complexes with the closed form of the HIV–1 protease and meta–stable intermediate complexes with the alternative structural forms of the protease. We have found that formation of the hydrophobic interaction clusters with the conserved flap residues may stabilize semi–open and open forms of the enzyme and lead to weakly bound, transient inhibitor complexes. The results suggest that inhibitors may function through a multi-mechanistic effect of stabilizing structurally different conformational states of the protease, highlighting the molecular basis of the flap residues in developing drug resistance.
100. Coarse-grained modeling of the HIV-1 protease binding mechanisms: II. Folding inhibition.
     Verkhivker G. Computational Intelligence Methods for Bioinformatics and Biostatistics. 2009. WOSUID: WOS:000268882700002
     Abstract

     Evolutionary and structurally conserved fragments 24–34 and 83–93 from each of the HIV–1 protease (HIV–1 PR) monomers constitute the critical components of the HIV–1 PR folding nucleus. It has been recently discovered that the peptide with the amino acid sequence NIIGRNLLTQI identical to the corresponding segment 83–93 of the HIV–1 PR monomer, can inhibit folding of HIV–1 PR. We have previously shown that this peptide can form stable complexes with the folded HIV–1 PR monomer by targeting the conserved segment 24–34 of the folding nucleus (folding inhibition) and by interacting with the antiparallel termini β–sheet region (dimerization inhibition). In this follow-up study, we propose a generalized, coarse–grained model of the folding inhibition based simulations with an ensemble of both folded and partially unfolded HIV–1 PR conformational states. Using a dynamic equilibrium between low–energy complexes formed with the folded and partially unfolded HIV–1 PR monomers, the NIIGRNLLTQI peptide may effectively intervene with the HIV–1 PR folding and dimerization. The performed microscopic analysis reconciles the experimental and computational results and rationalizes the molecular basis of folding inhibition.
101. Computational Modeling of Structurally Conserved Cancer Mutations in the RET and MET Kinases: The Impact on Protein Structure, Dynamics, and Stability.
     Dixit A, Torkamani A, Schork N. J, Verkhivker, G. Biophys J. 2009, 96,3,858-74. doi: 10.1016/j.bpj.2008.10.041.
     Abstract

     Structural and biochemical characterization of protein kinases that confer oncogene addiction and harbor a large number of disease-associated mutations, including RET and MET kinases, have provided insights into molecular mechanisms associated with the protein kinase activation in human cancer. In this article, structural modeling, molecular dynamics, and free energy simulations of a structurally conserved mutational hotspot, shared by M918T in RET and M1250T in MET kinases, are undertaken to quantify the molecular mechanism of activation and the functional role of cancer mutations in altering protein kinase structure, dynamics, and stability. The mechanistic basis of the activating RET and MET cancer mutations may be driven by an appreciable free energy destabilization of the inactive kinase state in the mutational forms. According to our results, the locally enhanced mobility of the cancer mutants and a higher conformational entropy are counterbalanced by a larger enthalpy loss and result in the decreased thermodynamic stability. The computed protein stability differences between the wild-type and cancer kinase mutants are consistent with circular dichroism spectroscopy and differential scanning calorimetry experiments. These results support the molecular mechanism of activation, which causes a detrimental imbalance in the dynamic equilibrium shifted toward the active form of the enzyme. Furthermore, computer simulations of the inhibitor binding with the oncogenic and drug-resistant RET mutations have also provided a plausible molecular rationale for the observed differences in the inhibition profiles, which is consistent with the experimental data. Finally, structural mapping of RET and MET cancer mutations and the computed protein stability changes suggest a similar mechanism of activation, whereby the cancer mutations which display the higher oncogenic activity tend to have the greatest destabilization effect on the inactive kinase structure.
102. Computational proteomics analysis of binding mechanisms and molecular signatures of the HIV-1 protease drugs.
     Verkhivker G. Artif Intell Med. 2009, 45,2-3,197-206. doi: 10.1016/j.artmed.2008.08.011.
     Abstract

     Computational proteomics analysis of biomolecular interactions is proposed to determine molecular signatures of the HIV-1 protease inhibitors. A comparative microscopic analysis is conducted for a panel of inhibitors which exemplify a diversity of the HIV-1 PR binding mechanisms, from the active site inhibition to intervening with the protease folding and dimerization. Replica-exchange Monte Carlo simulations with the conformational ensembles of the HIV-1 PR dimer and monomer structures enable a molecular analysis underlying diversity of the HIV-1 PR binding mechanisms. We have investigated the molecular basis underlying diversity of the HIV-1 PR binding mechanisms. The molecular basis of the HIV-1 PR active site and dimerization inhibition mechanisms has been analyzed for an active site tripeptide inhibitor and a tetrapeptide inhibitor, which can act as both a dimerization inhibitor and a competitive active site inhibitor. We have also simulated a structural mimicry mechanism of the HIV-1 PR folding inhibition and dimerization, according to which the folding inhibitor targets the conserved HIV-1 PR regions by mimicking the interaction network of the active dimer. We have shown that binding interfaces of the studied dimerization and folding HIV-1 PR inhibitors may enable structural mimicry with the hot spot residues of the HIV-1 PR dimer. The proposed structural models of intervening with the HIV-1 PR dimerization and folding support the mechanism of structural mimicry, which may alleviate drug resistance effects.
103. Hierarchical Modeling of Activation Mechanisms in the ABL and EGFR Kinase Domains: Thermodynamic and Mechanistic Catalysts of Kinase Activation by Cancer Mutations.
     Dixit A, Verkhivker G. PLoS Comput Biol. 2009, 5,8,e1000487. doi: 10.1371/journal.pcbi.1000487.
     Abstract

     Structural and functional studies of the ABL and EGFR kinase domains have recently suggested a common mechanism of activation by cancer-causing mutations. However, dynamics and mechanistic aspects of kinase activation by cancer mutations that stimulate conformational transitions and thermodynamic stabilization of the constitutively active kinase form remain elusive. We present a large-scale computational investigation of activation mechanisms in the ABL and EGFR kinase domains by a panel of clinically important cancer mutants ABL-T315I, ABL-L387M, EGFR-T790M, and EGFR-L858R. We have also simulated the activating effect of the gatekeeper mutation on conformational dynamics and allosteric interactions in functional states of the ABL-SH2-SH3 regulatory complexes. A comprehensive analysis was conducted using a hierarchy of computational approaches that included homology modeling, molecular dynamics simulations, protein stability analysis, targeted molecular dynamics, and molecular docking. Collectively, the results of this study have revealed thermodynamic and mechanistic catalysts of kinase activation by major cancer-causing mutations in the ABL and EGFR kinase domains. By using multiple crystallographic states of ABL and EGFR, computer simulations have allowed one to map dynamics of conformational fluctuations and transitions in the normal (wild-type) and oncogenic kinase forms. A proposed multi-stage mechanistic model of activation involves a series of cooperative transitions between different conformational states, including assembly of the hydrophobic spine, the formation of the Src-like intermediate structure, and a cooperative breakage and formation of characteristic salt bridges, which signify transition to the active kinase form. We suggest that molecular mechanisms of activation by cancer mutations could mimic the activation process of the normal kinase, yet exploiting conserved structural catalysts to accelerate a conformational transition and the enhanced stabilization of the active kinase form. The results of this study reconcile current experimental data with insights from theoretical approaches, pointing to general mechanistic aspects of activating transitions in protein kinases.
104. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface.
     Masulli F, Tagliaferri R, Verkhivker G. Lecture Notes in Computer Science. 2009. EID: 2-s2.0-70349319576
105. Modeling Signal Propagation Mechanisms and Ligand-Based Conformational Dynamics of the Hsp90 Molecular Chaperone Full-Length Dimer.
     Morra G, Verkhivker G, Colombo G. PLoS Comput Biol. 2009, 5,3,e1000323. doi: 10.1371/journal.pcbi.1000323.
     Abstract

     Hsp90 is a molecular chaperone essential for protein folding and activation in normal homeostasis and stress response. ATP binding and hydrolysis facilitate Hsp90 conformational changes required for client activation. Hsp90 plays an important role in disease states, particularly in cancer, where chaperoning of the mutated and overexpressed oncoproteins is important for function. Recent studies have illuminated mechanisms related to the chaperone function. However, an atomic resolution view of Hsp90 conformational dynamics, determined by the presence of different binding partners, is critical to define communication pathways between remote residues in different domains intimately affecting the chaperone cycle. Here, we present a computational analysis of signal propagation and long-range communication pathways in Hsp90. We carried out molecular dynamics simulations of the full-length Hsp90 dimer, combined with essential dynamics, correlation analysis, and a signal propagation model. All-atom MD simulations with timescales of 70 ns have been performed for complexes with the natural substrates ATP and ADP and for the unliganded dimer. We elucidate the mechanisms of signal propagation and determine “hot spots” involved in interdomain communication pathways from the nucleotide-binding site to the C-terminal domain interface. A comprehensive computational analysis of the Hsp90 communication pathways and dynamics at atomic resolution has revealed the role of the nucleotide in effecting conformational changes, elucidating the mechanisms of signal propagation. Functionally important residues and secondary structure elements emerge as effective mediators of communication between the nucleotide-binding site and the C-terminal interface. Furthermore, we show that specific interdomain signal propagation pathways may be activated as a function of the ligand. Our results support a “conformational selection model” of the Hsp90 mechanism, whereby the protein may exist in a dynamic equilibrium between different conformational states available on the energy landscape and binding of a specific partner can bias the equilibrium toward functionally relevant complexes.
106. Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases.
     Dixit A, Yi L, Gowthaman R, Torkamani A, Schork N. J, Verkhivker G. Plos One. 2009,  4,10,e7485. doi: 10.1371/journal.pone.0007485.
     Abstract

     Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis.
107. Structural and Computational Biology of the Molecular Chaperone Hsp90: From Understanding Molecular Mechanisms to Computer-Based Inhibitor Design.
     Verkhivker G, Dixit A, Morra G, Colombo G. Curr Top Med Chem. 2009, 9,15,1369-85. doi: 10.2174/156802609789895700.
     Abstract

     The molecular chaperone Hsp90 (90 kDa heat-shock protein) mediates many fundamental cellular pathways involved in cell proliferation, cell survival, and cellular stress response. Hsp90 is responsible for the correct conformational development, stability and function in crowded cell environments. Structural and computational biology studies have recently provided important insights into underlying molecular mechanisms of Hsp90 function. These developments have revealed a critical role of Hsp90 structure, conformational dynamics and interdomain communication in promoting the binding and release of ligands and its interaction with client proteins. By disabling multiple signal transduction pathways, Hsp90 inhibition provides a powerful therapeutic strategy in cancer research, which is selective for specific cancer mechanisms, yet broadly applicable to disparate tumors with different genetic signatures. Herein, we review the recent developments in structural and computational studies of Hsp90 function and binding, with the emphasis on progress towards computational structure-based discovery and design of Hsp90 inhibitors. We also review the emerging insights from computational and structure-based approaches to develop anticancer therapies that can target novel allosteric binding sites and Hsp90 interactions with co-chaperones and client proteins. Structural and computational biology studies can provide a foundation for the design of Hsp90 modulators capable of regulating functional protein motions linked to biological activities. We highlight current challenges in translating molecular mechanisms of the molecular chaperone into therapeutic strategies and outline future directions for the computer-based design of Hsp90 inhibitors.
108. The Role of Covalent Dimerization on the Physical and Chemical Stability of the EC1 Domain of Human E-Cadherin.
     Trivedi M, Davis R. A, Shabaik Y, Roy A, Verkhivker G, Laurence J. S, Middaugh C. R, Siahaan T. J. Journal of Pharmaceutical Sciences. 2009, 98,10,3562-74. doi: 10.1002/jps.21686.
     Abstract

     The objective of this work was to evaluate the solution stability of the EC1 domain of E-cadherin under various conditions. The EC1 domain was incubated at various temperatures (4, 37, and 70°C) and pH values (3.0, 7.0, and 9.0). At pH 9.0 and 37 or 70°C, a significant loss of EC1 was observed due to precipitation and a hydrolysis reaction. The degradation was suppressed upon addition of dithiothreitol (DTT), suggesting that the formation of EC1 dimer facilitated the EC1 degradation. At 4°C and various pH values, the EC1 secondary and tertiary showed changes upon incubation up to 28 days, and DTT prevented any structural changes upon 28 days of incubation. Molecular dynamics simulations indicated that the dimer of EC1 has higher mobility than does the monomer; this higher mobility of the EC1 dimer may contribute to instability of the EC1 domain.

2008

85. Atomistic simulations of the HIV-1 protease folding inhibition.
    Verkhivker G, Tiana G, Camilloni C, Provasi D, Broglia R. A. Biophysical Journal. 2008, 95,2,550-62. doi: 10.1529/biophysj.107.127621.
    Abstract

    Biochemical experiments have recently revealed that the p-S8 peptide, with an amino-acid sequence identical to the conserved fragment 83–93 (S8) of the HIV-1 protease, can inhibit catalytic activity of the enzyme by interfering with protease folding and dimerization. In this study, we introduce a hierarchical modeling approach for understanding the molecular basis of the HIV-1 protease folding inhibition. Coarse-grained molecular docking simulations of the flexible p-S8 peptide with the ensembles of HIV-1 protease monomers have revealed structurally different complexes of the p-S8 peptide, which can be formed by targeting the conserved segment 24–34 (S2) of the folding nucleus (folding inhibition) and by interacting with the antiparallel termini β-sheet region (dimerization inhibition). All-atom molecular dynamics simulations of the inhibitor complexes with the HIV-1 PR monomer have been independently carried out for the predicted folding and dimerization binding modes of the p-S8 peptide, confirming the thermodynamic stability of these complexes. Binding free-energy calculations of the p-S8 peptide and its active analogs are then performed using molecular dynamics trajectories of the peptide complexes with the HIV-1 PR monomers. The results of this study have provided a plausible molecular model for the inhibitor intervention with the HIV-1 PR folding and dimerization and have accurately reproduced the experimental inhibition profiles of the active folding inhibitors.
86. Structural modifications of ICAM-1 cyclic peptides to improve the activity to inhibit heterotypic adhesion of T cells.
    Iskandarsyah, Tejo B. A, Tambunan U. S. F, Verkhivker G, Siahaan T. J. Chemical Biology & Drug Design. 2008, 72,1,27-33. doi: 10.1111/j.1747-0285.2008.00676.x.
    Abstract

    Lymphocyte function-associated antigen-1 (LFA-1)/intercellular adhesion molecule-1 (ICAM-1) interaction plays an important role in the formation of the immunological synapse between T cells and antigen-presenting cells. Blocking of LFA-1/ICAM-1 interactions has been shown to suppress the progression of autoimmune diseases. cIBR peptide (cyclo(1,12)PenPRGGSVLVTGC) inhibits ICAM-1/LFA-1 interaction by binding to the I-domain of LFA-1. To increase the bioactivity of cIBR peptide, we systemically modified the structure of the peptide by (i) replacing the Pen residue at the N-terminus with Cys, (ii) cyclization using amide bond formation between Lys-Glu side chains, and (iii) reducing the peptide size by eliminating the C-terminal residue. We found that the activity of cIBR peptide was not affected by replacing Phe with Cys. Peptide cyclization by forming the Lys-Glu amide bond also increased the activity of cIBR peptide, presumably due to the resistance of the amide bond to the reducing nature of glutathione in plasma. We also found that a reduced derivative of cIBR with eight residues (cyclo(1,8)CPRGGSVC) has a bioactivity similar to that of the larger cIBR peptides. Our findings suggest that, by systemically modifying the structure of cIBR peptide, the biological activity of these derivatives can be optimized for future use to inhibit T-cell adhesion in in vivo models of autoimmune diseases.
87. Understanding ligand-based modulation of the Hsp90 molecular chaperone dynamics at atomic resolution.
    Colombo G, Morra G, Meli M, Verkhivker G. Proceedings of the National Academy of Sciences of the United States of America. 2008, 105,23,7976-81. doi: 10.1073/pnas.0802879105.
    Abstract

    Molecular switching and ligand-based modulation of the 90-kDa heat-shock protein (Hsp90) chaperone activity may ultimately facilitate conformational coupling to the ATPase cycle along with activation and recruitment of the broad range of client proteins. We present an atomic resolution analysis of the Hsp90 N-terminal domain (NTD) binding energy landscape by simulating protein dynamics with a range of binding partners. We show that the activity of the molecular chaperone may be linked to (i) local folding-unfolding transitions and conformational switching of the “active site lid” upon binding and (ii) differences in the underlying protein dynamics as a function of the binding partner. This study suggests that structural plasticity of the Hsp90 NTD can be exploited by the molecular chaperone machinery to modulate enhanced structural rigidity during ATP binding and increased protein flexibility as a consequence of the inhibitor binding. The present study agrees with the experimental structural data and provides a plausible molecular model for understanding mechanisms of modulation of molecular chaperone activities by binding partners.

2007

82. Computational proteomics of biomolecular interactions in sequence and structure space of the tyrosine kinome: Evolutionary constraints and protein conformational selection determine binding signatures of cancer drugs.
    Verkhivker, G. Lecture Notes in Computer Science. 2007, p.604-611. EID: 2-s2.0-37249026752
    Abstract

    The emerging insights into kinase function and evolution combined with a rapidly growing number of crystal structures of protein kinases complexes have facilitated a comprehensive structural bioinformatics analysis of sequence—structure relationships in determining the binding function of protein tyrosine kinases. We have found that evolutionary signal derived solely from the tyrosine kinase sequence conservation can not be readily translated into the ligand binding phenotype. However, fingerprinting ligand—protein interactions using in silico profiling of inhibitor binding against protein tyrosine kinases crystal structures can detect a functionally relevant kinase binding signal and reconcile the existing experimental data. In silico proteomics analysis unravels mechanisms by which structural plasticity of the tyrosine kinases is linked with the conformational preferences of cancer drugs Imatinib and Dasatinib in achieving effective drug binding with a distinct spectrum of the tyrosine kinome. While Imatinib binding is highly sensitive to the activation state of the enzyme, the computed binding profile of Dasatinib is remarkably tolerant to the conformational state of ABL. A comprehensive study of evolutionary, structural, dynamic and energetic aspects of tyrosine kinases binding with clinically important class of inhibitors provides important insights into mechanisms of sequence—structure relationships in the kinome space and molecular basis of functional adaptability towards specific binding.
83. Computational proteomics of biomolecular interactions in the sequence and structure space of the tyrosine kinome: Deciphering the molecular basis of the kinase inhibitors selectivity.
    Verkhivker G. Proteins-Structure Function and Bioinformatics. 2007, 66,4,912-29. doi: 10.1002/prot.21287.
    Abstract

    Understanding and predicting the molecular basis of protein kinases specificity against existing therapeutic agents remains highly challenging and deciphering this complexity presents an important problem in discovery and development of effective cancer drugs. We explore a recently introduced computational approach for in silico profiling of the tyrosine kinases binding specificity with a class of the pyrido-[2,3-d]pyrimidine kinase inhibitors. Computational proteomics analysis of the ligand–protein interactions using parallel simulated tempering with an ensemble of the tyrosine kinases crystal structures reveals an important molecular determinant of the kinase specificity. The pyrido-[2,3-d]pyrimidine inhibitors are capable of dynamically interacting with both active and inactive forms of the tyrosine kinases, accommodating structurally different kinase conformations with a similar binding affinity. Conformational tolerance of the protein tyrosine kinases binding with the pyrido[2,3-d]pyrimidine inhibitors provides the molecular basis for the broad spectrum of potent activities and agrees with the experimental inhibition profiles. The analysis of the pyrido[2,3-d]pyrimidine sensitivities against a number of clinically relevant ABL kinase mutants suggests an important role of conformational adaptability of multitargeted kinase inhibitors in developing drug resistance mechanisms. The presented computational approach may be useful in complementing proteomics technologies to characterize activity signatures of small molecules against a large number of potential kinase targets.
84. Computational structural proteomics of the kinases binding specificity and drug resistance.
    Verkhivker G. Proceedings of the International School of Physics “Enrico Fermi”. 2007. EID: 2-s2.0-84884611965
85. Energy landscapes of bimolecular binding and molecular modulators of protein-protein interactions.
    Verkhivker G. Proceedings of the International School of Physics “Enrico Fermi”. 2007. EID: 2-s2.0-84884648721 
86. Exploring mechanisms of protein folding and binding in signal transduction networks.
    Verkhivker G. Proceedings of the International School of Physics “Enrico Fermi”. 2007. EID: 2-s2.0-84884607010
87. Exploring sequence-structure relationships in the tyrosine kinome space: functional classification of the binding specificity mechanisms for cancer therapeutics.
    Verkhivker G. Bioinformatics. 2007, 23,15,1919-26. doi: 10.1093/bioinformatics/btm277.
    Abstract

    Evolutionary and structural conservation patterns shared by more than 500 of identified protein kinases have led to complex sequence-structure relationships of cross-reactivity for kinase inhibitors. Understanding the molecular basis of binding specificity for protein kinases family, which is the central problem in discovery of cancer therapeutics, remains challenging as the inhibitor selectivity is not readily interpreted from chemical proteomics studies, neither it is easily discernable directly from sequence or structure information. We present an integrated view of sequence-structure-binding relationships in the tyrosine kinome space in which evolutionary analysis of the kinases binding sites is combined with computational proteomics profiling of the inhibitor–protein interactions. This approach provides a functional classification of the binding specificity mechanisms for cancer agents targeting protein tyrosine kinases. The proposed functional classification of the kinase binding specificities explores mechanisms in which structural plasticity of the tyrosine kinases and sequence variation of the binding-site residues are linked with conformational preferences of the inhibitors in achieving effective drug binding. The molecular basis of binding specificity for tyrosine kinases may be largely driven by conformational adaptability of the inhibitors to an ensemble of structurally different conformational states of the enzyme, rather than being determined by their phylogenetic proximity in the kinome space or differences in the interactions with the variable binding-site residues. This approach provides a fruitful functional linkage between structural bioinformatics analysis and disease by unraveling the molecular basis of kinase selectivity for the prominent kinase drugs (Imatinib, Dasatinib and Erlotinib) which is consistent with structural and proteomics experiments
88. In silico profiling of tyrosine kinases binding specificity and drug resistance using Monte Carlo simulations with the ensembles of protein kinase crystal structures.
    Verkhivker G. Biopolymers. 2007, 85,4,333-48. doi: 10.1002/bip.20656.
    Abstract

    The molecular basis of the tyrosine kinases binding specificity and drug resistance against cancer drugs Imatinib and Dasatinib is elucidated using Monte Carlo simulations of the inhibitor-receptor binding with the ensembles of protein kinase crystal structures. In silico proteomics analysis unravels mechanisms by which structural plasticity of the tyrosine kinases is linked with the conformational preferences of Imatinib and Dasatinib in achieving effective drug binding with a distinct spectrum of the tyrosine kinome. The differences in the inhibitor sensitivities to the ABL kinase mutants are rationalized based on variations in the binding free energy profiles with the conformational states of the ABL kinase. While Imatinib binding is highly sensitive to the activation state of the enzyme, the computed binding profile of Dasatinib is remarkably tolerant to the conformational state of ABL. A comparative analysis of the inhibitor binding profiles with the clinically important ABL kinase mutants has revealed an excellent agreement with the biochemical and proteomics data. We have found that conformational adaptability of the kinase inhibitors to structurally different conformational states of the tyrosine kinases may have pharmacological relevance in acquiring a specific array of potent activities and regulating a scope of the inhibitor resistance mutations. This study outlines a useful approach for understanding and predicting the molecular basis of the inhibitor sensitivity against potential kinase targets and drug resistance.
89. Quantifying intrinsic specificity: A potential complement to affinity in drug screening.
    Wang J, Zheng X, Yang Y, Drueckhammer D, Yang W, Verkhivker G, Wang E. Physical Review Letters. 2007, 99,19,198101. doi: 10.1103/PhysRevLett.99.198101.
    Abstract

    We report here the investigation of a novel description of specificity in protein-ligand binding based on energy landscape theory. We define a new term, intrinsic specificity ratio (ISR), which describes the level of discrimination in binding free energies of the native basin for a protein-ligand complex from the weaker binding states of the same ligand. We discuss the relationship between the intrinsic specificity we defined here and the conventional definition of specificity. In a docking study of molecules with the enzyme COX-2, we demonstrate a statistical correspondence between ISR value and geometrical shapes of the small molecules binding to COX-2. We further observe that the known selective (nonselective) inhibitors of COX-2 have higher (lower) ISR values. We suggest that intrinsic specificity ratio may be a useful new criterion and a complement to affinity in drug screening and in searching for potential drug lead compounds.
90. Sequence recognition of alpha-LFA-1-derived peptides by ICAM-1 cell receptors: Inhibitors of T-cell adhesion.
    Yusuf-Makagiansar H, Yakovleva T. V, Tejo B. A, Jones K, Hu Y. B, Verkhivker G, Audus K. L, Siahaan T. J. Chemical Biology & Drug Design. 2007, 70,3,237-46. doi: 10.1111/j.1747-0285.2007.00549.x.
    Abstract

    Blocking the T-cell adhesion signal from intercellular adhesion molecule-1/leukocyte function-associated antigen-1 interactions (Signal-2) can suppress the progression of autoimmune diseases (i.e. type-1 diabetes, psoriasis) and prevent allograph rejection. In this study, we determined the active region(s) of cLAB.L peptide [cyclo(1,12)Pen-ITDGEATDSGC] by synthesizing and evaluating the biologic activity of hexapeptides in inhibiting T-cell adhesion. A new heterotypic T-cell adhesion assay was also developed to provide a model for the T-cell adhesion process during lung inflammation. Two hexapeptides, ITDGEA and DGEATD, were found to be more active than the other linear hexapeptides. The cyclic derivative of ITDGEA [i.e. cyclo(1,6)ITDGEA] has similar activity than the parent linear peptide and has lower activity than cLAB.L peptide. Computational-binding experiments were carried out to explain the possible mechanism of binding of these peptides to intercellular adhesion molecule-1. Both ITDGEA and DGEATD bind the same site on intercellular adhesion molecule-1 and they interact with the Gln34 and Gln73 residues on D1 of intercellular adhesion molecule-1. In the future, more potent derivatives of cyclo(1,6)ITDGEA will be designed by utilizing structural and binding studies of the peptide to intercellular adhesion molecule-1. The heterotypic T-cell adhesion to Calu-3 will also be used as another assay to evaluate the selectivity of the designed peptides.

2006

73. BIOT 198-Quantifying intrinsic specificity: A potential complement to affinity in drug screening.
    Wang J, Yang Y. L, Yang W Drueckhammer, D. G, Verkhivker G. Abstracts of Papers of the American Chemical Society. 2006.
    Abstract

    We report here the investigation of a novel description of specificity in protein-ligand binding based on energy landscape theory. We define a new term, intrinsic specificity ratio (ISR), which describes the level of discrimination in binding free energies of the native basin for a protein-ligand complex from the weaker binding states of the same ligand. We discuss the relationship between the intrinsic specificity we defined here and the conventional definition of specificity. In a docking study of molecules with the enzyme COX-2, we demonstrate a statistical correspondence between ISR value and geometrical shapes of the small molecules binding to COX-2. We further observe that the known selective (nonselective) inhibitors of COX-2 have higher (lower) ISR values. We suggest that intrinsic specificity ratio may be a useful new criterion and a complement to affinity in drug screening and in searching for potential drug lead compounds.
74. Imprint of evolutionary conservation and protein structure variation on the binding function of protein tyrosine kinases.
    Verkhivker G. Bioinformatics. 2006, 22,15,1846-54. doi: 10.1093/bioinformatics/btl199.
    Abstract

    According to the models of divergent molecular evolution, the evolvability of new protein function may depend on the induction of new phenotypic traits by a small number of mutations of the binding site residues. Evolutionary relationships between protein kinases are often employed to infer inhibitor binding profiles from sequence analysis. However, protein kinases binding profiles may display inhibitor selectivity within a given kinase subfamily, while exhibiting cross-activity between kinases that are phylogenetically remote from the prime target. The emerging insights into kinase function and evolution combined with a rapidly growing number of publically available crystal structures of protein kinases complexes have motivated structural bioinformatics analysis of sequence–structure relationships in determining the binding function of protein tyrosine kinases. In silico profiling of Imatinib mesylate and PD-173955 kinase inhibitors with protein tyrosine kinases is conducted on kinome scale by using evolutionary analysis and fingerprinting inhibitor–protein interactions with the panel of all publically available protein tyrosine kinases crystal structures. We have found that sequence plasticity of the binding site residues alone may not be sufficient to enable protein tyrosine kinases to readily evolve novel binding activities with inhibitors. While evolutionary signal derived solely from the tyrosine kinase sequence conservation can not be readily translated into the ligand binding phenotype, the proposed structural bioinformatics analysis can discriminate a functionally relevant kinase binding signal from a simple phylogenetic relationship. The results of this work reveal that protein conformational diversity is intimately linked with sequence plasticity of the binding site residues in achieving functional adaptability of protein kinases towards specific drug binding. This study offers a plausible molecular rationale to the experimental binding profiles of the studied kinase inhibitors and provides a theoretical basis for constructing functionally relevant kinase binding trees.

2005

71. A microscopic study of disorder-order transitions in molecular recognition of unstructured proteins: Hierarchy of structural loss and the transition state determination from Monte Carlo simulations of P27^KIP1 protein coupled unfolding and unbinding.
    Verkhivker G. Supramolecular Structure and Function 8. 2005. doi: 10.1007/0-306-48662-8_12
72. Computational detection of the binding site hot spot and predicting energetics of ligand binding at the remodeled human growth hormone-receptor interface using a hierarchy of molecular docking and binding free energy approaches.
    Verkhivker G. Supramolecular Structure and Function 8. 2005. doi: 10.1007/0-306-48662-8_13
73. Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: Deciphering the effect of intermolecular interactions on computational structure prediction of the p27Kip1 protein bound to the cyclin A-cyclin-dependent kinase 2 complex.
    Verkhivker G. Proteins-Structure Function and Bioinformatics. 2005. doi: 10.1002/prot.20351
    Abstract

    The relationship between folding mechanism coupled to binding and structure prediction of the tertiary complexes is studied for the p27Kip1 protein which has an intrinsically disordered unbound form and undergoes a functional folding transition during complex formation with the phosphorylated cyclin A–cyclin-dependent kinase 2 (Cdk2) binary complex. Hierarchy of p27Kip1 structural loss determined in our earlier studies from temperature–induced Monte Carlo simulations and subsequent characterization of the transition state ensemble (TSE) for the folding reaction have shown that simultaneous ordering of the p27Kip1 native intermolecular interface for the β-hairpin and β-strand secondary structure elements is critical for nucleating a rapid kinetic transition to the native tertiary complex. In the present study, we investigate the effect of forming specific intermolecular interactions on structure prediction of the p27Kip1 tertiary complex. By constraining different secondary structure elements of p27Kip1 in their native bound conformations and conducting multiple simulated annealing simulations, we analyze differences in the success rate of predicting the native structure of p27Kip1 in the tertiary complex. In accordance with the nucleation–condensation mechanism, we have found that further stabilization of the native intermolecular interface for the β-hairpin and β-strand elements of p27Kip1, that become ordered in the TSE, but are hardly populated in the unbound state, results in a consistent acquisition of the native bound structure. Conversely, the excessive stablization of the local secondary structure elements, which are rarely detected in the TSE, has a detrimental effect on convergence to the native bound structure.

2004

68. Computational analysis of ligand binding dynamics at the intermolecular hot spots with the aid of simulated tempering and binding free energy calculations.
    Verkhivker G. Journal of Molecular Graphics & Modelling. 2004, 22,5,335-48. doi: 10.1016/j.jmgm.2003.12.001.
    Abstract

    Equilibrium binding dynamics is studied for a panel of benzimidazole-containing compounds at the remodeled interface between human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp), engineered by mutating to glycine hot spot residues T175 from the hormone and W104 from the receptor. Binding energetics is predicted in a good agreement with the experimental data for a panel of these small molecules that complement the engineered defect and restore the binding affinity of the wild-type hGH–hGHbp complex. The results of simulated tempering ligand dynamics at the protein–protein interface reveals a diversity of ligand binding modes that is consistent with the structural orientation of the benzimidazole ring which closely mimics the position of the mutated W104 hot spot residue in the wild-type hGH–hGHbp complex. This structural positioning of the benzimidazole core motif is shown to be a critical feature of the low-energy ligand conformations binding in the engineered cavity. The binding free energy analysis provides a plausible rationale behind the experimental dissociation constants and suggests a key role of ligand–protein van der Waals interactions in restoring binding affinity.
69. Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: Hierarchy of structural loss from all-atom Monte Carlo Simulations of p27(Kip1) unfolding-unbinding and structural determinants of the binding mechanism.
    Verkhivker G. Biopolymers. 2004. doi: 10.1002/bip.20149
    Abstract

    Conformational transitions coupled to binding are studied for the p27Kip1 protein which undergoes a functional disorder–to–order folding transition during tertiary complex formation with the phosphorylated cyclin A–cyclin-dependent kinase 2 (Cdk2) binary complex. Temperature–induced Monte Carlo simulations of p27Kip1 unfolding–unbinding carried out from the crystal structure of the tertiary complex have revealed a systematic trend in the hierarchy of structural loss for p27Kip1 and a considerable difference in mobility of p27Kip1 secondary structure elements. The most persistent interactions of p27Kip1 at the intermolecular interface during unfolding–unbinding simulations are formed by β-hairpin and β–strand that on average maintain their structural integrity considerably longer than other p27Kip1 elements. We have found that the ensemble of unfolded p27Kip1 conformations is characterized by transitions between mostly unbound, collapsed conformations and entropically favorable p27Kip1 conformations, which are weakly bound to the cyclin A side of the binary complex. The results of this study are consistent with the experimental evidence pointing to this region of the intermolecular interface as a potential initiation docking site during binding reaction and may reconcile conflicting experimental hypotheses on the recognition of substrate recruitment motifs.
70. The use of chemical recuperation of heat in a power plant.
    Verkhivker G. Energy. 2004. DOI: 10.1016/j.energy.2003.10.010
    Abstract

    Chemical recuperation of heat is the most considerable method of increasing the efficiency of combined-cycle plants, but plants with chemical recuperation are not in application yet. In this paper, the causes of this phenomenon have been examined and the thermodynamic basis of using chemical recuperation of heat has been given. The energy efficiency of a combined cycle plant with chemical recuperation has reached 80–90% and more and it increases with lower reforming pressure. Additionally, chemical recuperation has raised the amount of gas fuel used in energy and chemical industries and has decreased the amount of waste carbon dioxide ejected into the environment by nearly 20%. The energy efficiency of a power plant with chemical recuperation must be calculated with registration of the methane which does not undergo a reaction in the reformer.

2003

65. Computational detection of the binding-site hot spot at the remodeled human growth hormone-receptor interface.
    Verkhivker G, Bouzida D, Gehlhaar D. K, Rejto P. A, Freer S. T, Rose P. W. Proteins-Structure Function and Bioinformatics. 2003, 53,2,201-19. doi: 10.1002/prot.10456.
    Abstract

    A hierarchical computational approach is used to identify the engineered binding-site cavity at the remodeled intermolecular interface between the mutants of human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp). Multiple docking simulations are conducted with the remodeled hGH–hGHbp complex for a panel of potent benzimidazole-containing inhibitors that can restore the binding affinity of the wild-type complex, and for a set of known nonactive small molecules that contain different heterocyclic motifs. Structural clustering of ligand-bound conformations and binding free-energy calculations, using the AMBER force field and a continuum solvation model, can rapidly locate and screen numerous ligand-binding modes on the protein surface and detect the binding-site hot spot at the intermolecular interface. Structural orientation of the benzimidazole motif in the binding-site cavity closely mimics the position of the hot spot residue W104 in the crystal structure of the wild-type complex, which is recognized as an important structural requirement for restoring binding affinity. Despite numerous pockets on the protein surface of the mutant hGH–hGHbp complex, the binding-site cavity presents the energetically favorable hot spot for the benzimidazole-containing inhibitors, whereas for a set of nonactive molecules, the lowest energy ligand conformations do not necessarily bind in the engineered cavity. The results reveal a dominant role of the intermolecular van der Waals interactions in providing favorable ligand–protein energetics in the redesigned interface, in agreement with the experimental and computational alanine scanning of the hGH–hGHbp complex.
66. Energy landscape theory, funnels, specificity, and optimal criterion of biomolecular binding.
    Wang J, Verkhivker G. Physical Review Letters. 2003, 90,18,188101. doi: 10.1103/PhysRevLett.90.188101.
    Abstract

    We study the nature of biomolecular binding. We found that in general there exists several thermodynamic phases: a native binding phase, a non-native phase, and a glass or local trapping phase. The quantitative optimal criterion for the binding specificity is found to be the maximization of the ratio of the binding transition temperature versus the trapping transition temperature, or equivalently the ratio of the energy gap of binding between the native state and the average non-native states versus the dispersion or variance of the non-native states. This leads to a funneled binding energy landscape.
67. Simulating disorder-order transitions in molecular recognition of unstructured proteins: Where folding meets binding.
    Verkhivker G. Abstracts of Papers of the American Chemical Society. 2003, 100,9,5148-53. doi: 10.1073/pnas.0531373100.
    Abstract

    A microscopic study of functional disorder–order folding transitions coupled to binding is performed for the p27 protein, which derives a kinetic advantage from the intrinsically disordered unbound form on binding with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) complex. Hierarchy of structural loss during p27 coupled unfolding and unbinding is simulated by using high-temperature Monte Carlo simulations initiated from the crystal structure of the tertiary complex. Subsequent determination of the transition-state ensemble and the proposed atomic picture of the folding mechanism coupled to binding provide a microscopic rationale that reconciles the initiation recruitment of p27 at the cyclin A docking site with the kinetic benefit for a disordered α-helix in the unbound form of p27. The emerging structural polarization in the ensemble of unfolding/unbinding trajectories and in the computationally determined transition-state ensemble is not determined by the intrinsic folding preferences of p27 but rather is attributed to the topological requirements of the native intermolecular interface to order β-hairpin and β-strand of p27 that could be critical for nucleating rapid folding transition coupled to binding. In agreement with the experimental data, the disorder–order folding transition for p27 is largely determined by the functional requirement to form a specific intermolecular interface that ultimately dictates the folding mechanism and overwhelms any local folding preferences for creating a stable α-helix in the p27 structure before overcoming the major free energy barrier.

2002

62. Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective.
    Verkhivker G, Bouzida D, Gehlhaar D.K, Rejto P. A, Freer S. T, Rose P. W. Current Opinion in Structural Biology. 2002, 12,2,197-203. doi: 10.1016/s0959-440x(02)00310-x.
    Abstract

    The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand–macromolecule interactions. Significant advances in computational structure prediction of ligand–protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes.
63. Computer simulations of molecular recognition using generalized-ensemble Monte Carlo methods.
    Verkhivker G. Abstracts of Papers of the American Chemical Society. 2002. WOSUID: WOS:000176296702832
64. Hierarchy of simulation models in predicting structure and energetics of the Src SH2 domain binding to tyrosyl phosphopeptides.
    Verkhivker G,  Bouzida D, Gehlhaar D. K, Rejto P. A, Schaffer L, Arthurs S, Colson A. B, Freer S. T, Larson V Luty B. A, et al. Journal of Medicinal Chemistry. 2002, 45,1,72-89. doi: 10.1021/jm0101141
    Abstract

    Structure and energetics of the Src Src Homology 2 (SH2) domain binding with the recognition phosphopeptide pYEEI and its mutants are studied by a hierarchical computational approach. The proposed structure prediction strategy includes equilibrium sampling of the peptide conformational space by simulated tempering dynamics with the simplified, knowledge-based energy function, followed by structural clustering of the resulting conformations and binding free energy evaluation of a single representative from each cluster, a cluster center. This protocol is robust in rapid screening of low-energy conformations and recovers the crystal structure of the pYEEI peptide. Thermodynamics of the peptide−SH2 domain binding is analyzed by computing the average energy contributions over conformations from the clusters, structurally similar to the predicted peptide bound structure. Using this approach, the binding thermodynamics for a panel of studied peptides is predicted in a better agreement with the experiment than previously suggested models. However, the overall correlation between computed and experimental binding affinity remains rather modest. The results of this study show that small differences in binding free energies between the Ala and Gly mutants of the pYEEI peptide are considerably more difficult to predict than the structure of the bound peptides, indicating that accurate computational prediction of binding affinities still remains a major methodological and technical challenge.
65. Monte Carlo simulations of the peptide recognition at the consensus binding site of the constant fragment of human immunoglobulin G: the energy landscape analysis of a hot spot at the intermolecular interface.
    Verkhivker G, Bouzida D, Gehlhaar D. K, Rejto P. A, Freer S. T, Rose P. W. Proteins-Structure Function and Bioinformatics. 2002, 48,3,539-57. doi: 10.1002/prot.10164
    Abstract

    Monte Carlo simulations of molecular recognition at the consensus binding site of the constant fragment (Fc) of human immunoglobulin G (Ig) protein have been performed to analyze structural and thermodynamic aspects of binding for the 13-residue cyclic peptide DCAWHLGELVWCT. The energy landscape analysis of a hot spot at the intermolecular interface using alanine scanning and equilibrium-simulated tempering dynamics with the simplified, knowledge-based energy function has enabled the role of the protein hot spot residues in providing the thermodynamic stability of the native structure to be determined. We have found that hydrophobic interactions between the peptide and the Met-252, Ile-253, His-433, and His-435 protein residues are critical to guarantee the thermodynamic stability of the crystallographic binding mode of the complex. Binding free energy calculations, using a molecular mechanics force field and a solvation energy model, combined with alanine scanning have been conducted to determine the energetic contribution of the protein hot spot residues in binding affinity. The conserved Asn-434, Ser-254, and Tyr-436 protein residues contribute significantly to the binding affinity of the peptide–protein complex, serving as an energetic hot spot at the intermolecular interface. The results suggest that evolutionary conserved hot spot protein residues at the intermolecular interface may be partitioned in fulfilling thermodynamic stability of the native binding mode and contributing to the binding affinity of the complex.
66. The problem of increasing the efficiency of combined-cycle plants.
    Verkhivker G,  Kravchenko V.P, Laguta S.M. Teploenergetika. 2002. EID: 2-s2.0-0036950383
67. The problem of increasing the efficiency of combined-cycle plants.
    Verkhivker G,  Kravchenko V.P, Laguta S.M. Thermal Engineering. 2002. EID: 2-s2.0-0036950383

2001

56. Conformational composition of 5-alkyl-1,3-oxathianes
    Turyanskaya A. M, Novikov A. N, Verkhivker G, Kuznetsov V. V. Russian Journal of General Chemistry. 2001, 71,9,1487-1490. doi: 10.1023/a:1013930725137
    Abstract

    Conformational equilibrium of 5-isopropyl-1,3-oxathiane occurs mainly between the forms of chair with equatorial and axial orientation of the substituent at the C5 atom, and in the case of 2,2,5-trimethyl- and, apparently, in the case of 5-tert-butyl-1,3-oxathianes is characterized by a more noticeable contribution of flexible forms.
57. Hierarchy of simulation models in predicting molecular recognition mechanisms from the binding energy landscapes.
    Verkhivker G. Abstracts of Papers of the American Chemical Society. 2001, 45,4,456-70. WOSUID: WOS:000170690001917
    Abstract

    Computer simulations using the simplified energy function and simulated tempering dynamics have accurately determined the native structure of the pYVPML, SVLpYTAVQPNE, and SPGEpYVNIEF peptides in the complexes with SH2 domains. Structural and equilibrium aspects of the peptide binding with SH2 domains have been studied by generating temperature-dependent binding free energy landscapes. Once some native peptide–SH2 domain contacts are constrained, the underlying binding free energy profile has the funnel-like shape that leads to a rapid and consistent acquisition of the native structure. The dominant native topology of the peptide–SH2 domain complexes represents an extended peptide conformation with strong specific interactions in the phosphotyrosine pocket and hydrophobic interactions of the peptide residues C-terminal to the pTyr group. The topological features of the peptide–protein interface are primarily determined by the thermodynamically stable phosphotyrosyl group. A diversity of structurally different binding orientations has been observed for the amino-terminal residues to the phosphotyrosine. The dominant native topology for the peptide residues carboxy-terminal to the phosphotyrosine is tolerant to flexibility in this region of the peptide–SH2 domain interface observed in equilibrium simulations. The energy landscape analysis has revealed a broad, entropically favorable topology of the native binding mode for the bound peptides, which is robust to structural perturbations. This could provide an additional positive mechanism underlying tolerance of the SH2 domains to hydrophobic conservative substitutions in the peptide specificity region.
58. Hierarchy of simulation models in predicting molecular recognition mechanisms from the binding energy landscapes: Structural analysis of the peptide complexes with SH2 domains.
    Verkhivker G, Bouzida D, Gehlhaar D. K, Rejto P. A, Schaffer L, Arthurs S, Colson A. B, Freer S.T, Larson V, Luty B. A. et al. Proteins-Structure Function and Bioinformatics. 2001, 45,4,456-70. doi: 10.1002/prot.10019
    Abstract

    Computer simulations using the simplified energy function and simulated tempering dynamics have accurately determined the native structure of the pYVPML, SVLpYTAVQPNE, and SPGEpYVNIEF peptides in the complexes with SH2 domains. Structural and equilibrium aspects of the peptide binding with SH2 domains have been studied by generating temperature-dependent binding free energy landscapes. Once some native peptide–SH2 domain contacts are constrained, the underlying binding free energy profile has the funnel-like shape that leads to a rapid and consistent acquisition of the native structure. The dominant native topology of the peptide–SH2 domain complexes represents an extended peptide conformation with strong specific interactions in the phosphotyrosine pocket and hydrophobic interactions of the peptide residues C-terminal to the pTyr group. The topological features of the peptide–protein interface are primarily determined by the thermodynamically stable phosphotyrosyl group. A diversity of structurally different binding orientations has been observed for the amino-terminal residues to the phosphotyrosine. The dominant native topology for the peptide residues carboxy-terminal to the phosphotyrosine is tolerant to flexibility in this region of the peptide–SH2 domain interface observed in equilibrium simulations. The energy landscape analysis has revealed a broad, entropically favorable topology of the native binding mode for the bound peptides, which is robust to structural perturbations. This could provide an additional positive mechanism underlying tolerance of the SH2 domains to hydrophobic conservative substitutions in the peptide specificity region.
59. Monte Carlo simulations of HIV-1 protease binding dynamics and thermodynamics with ensembles of protein conformations: Incorporating protein flexibility in deciphering mechanisms of molecular recognition.
    Verkhivker G, Bouzida D, Gehlhaar D. K, Rejto P. A, Schaffer L, Arthurs S, Colson A. B, Freer S.T, Larson V, Luty B. A. et al. Theoretical and Computational Chemistry. 2001, p.289-340. EID: 2-s2.0-0035785710
60. Navigating ligand-protein binding free energy landscapes: universality and diversity of protein folding and molecular recognition mechanisms.
    Verkhivker G. M, Rejto P. A, Bouzida D, Arthurs S, Colson A. B, Freer S. T, Gehlhaar D. K, Larson V, Luty B. A, Marrone T. et al. Chemical Physics Letters. 2001. doi: 10.1016/s0009-2614(01)00161-0
    Abstract

    Thermodynamic and kinetic aspects of ligand–protein binding are studied for the methotrexate–dihydrofolate reductase system from the binding free energy profile constructed as a function of the order parameter. Thermodynamic stability of the native complex and a cooperative transition to the unique native structure suggest the nucleation kinetic mechanism at the equilibrium transition temperature. Structural properties of the transition state ensemble and the ensemble of nucleation conformations are determined by kinetic simulations of the transmission coefficient and ligand–protein association pathways. Structural analysis of the transition states and the nucleation conformations reconciles different views on the nucleation mechanism in protein folding.
61. On the exergy analysis of power plants.
    Verkhivker G. P, Kosoy B. V. Energy Conversion and Management. 2001. doi: 10.1016/s0196-8904(00)00170-9
    Abstract

    The thermal performance of power generating and consuming devices can be improved significantly, both during design and operation. This is especially important in eastern and central European countries during their transition to a market environment. A solution can be sought by combining exergy and economic analyses. The performances of conventional power plants and nuclear power plants are discussed, based on the exergy concept. It is proposed to define the entire nuclear plant efficiency by the system coefficient of performance.
62. Parallel simulated tempering dynamics of ligand-protein binding with ensembles of protein conformations.
    Verkhivker G. M, Rejto P. A, Bouzida D, Arthurs S, Colson A. B, Freer S. T, Gehlhaar D. K, Larson V, Luty B. A, Marrone T. et al. Chemical Physics Letters. 2001. DOI: 10.1016/s0009-2614(01)00168-3
    Abstract

    Simulated tempering dynamics with the simplified energy model and the ensemble of protein conformations have been performed for the SB203386 inhibitor binding with HIV-1 protease. Equilibrium simulations with multiple protein conformations implicitly incorporate protein flexibility and rank HIV-1 protease conformations according to the average ligand–protein interaction energies. Subsequent energy refinement with a molecular mechanics force field accurately quantifies the energetics of the low-energy ligand binding modes. The results suggest that the mobility of the SB203386 inhibitor is effectively restricted to two symmetry-related binding modes and this may prevent the inhibitor from adapting to distorted binding sites in mutant conformations.
63. Zero-emissions gas-fired cogeneration of power and hydrogen.
    Verkhivker G, Yantovski E. International Journal of Hydrogen Energy. 2001. DOI: 10.1016/s0360-3199(01)00048-9son V, Luty B. A, Marrone T. et al. Chemical Physics Letters. 2001. DOI: 10.1016/s0009-2614(01)00168-3
    Abstract

    International Gas Union stated at the 21st World Gas Conference in June 2000 that even a small portion of gas reserves can cover world demand over 200 years at the current production rate. Hence, the dominant energy source in the coming century is to be natural gas with an increased role of convergence of gas and power industry on zero-emission basis. In the paper, a scheme of gas-fired cogeneration of power and hydrogen is presented. It is a further development of a quasicombined zero-emission power cycle, published earlier. As a new element, it includes the chemical recuperation by methane-steam conversion. Mass, energy and exergy balances, T–S diagram of CO2 part of the cycle and exergy efficiency in design point (89%) are presented. As it is essentially zero-emission, the plant might be located in a densely populated urban area for power, hydrogen and heat supply.

2000

48. Deciphering common failures in molecular docking of ligand-protein complexes.
    Verkhivker G. M, Rejto P. A, Bouzida D, Arthurs S, Colson A. B, Freer S. T, Gehlhaar D. K, Larson V, Luty B. A, Marrone T. et al. Journal of Computer-Aided Molecular Design. 2000, 14,8,731-51. doi: 10.1023/a:1008158231558
    Abstract

    Common failures in predicting crystal structures of ligand-protein complexes are investigated for three ligand-protein systems by a combined thermodynamic and kinetic analysis of the binding energy landscapes. Misdocked predictions in ligand-protein docking are classified as `soft’ and `hard’ failures. While a soft failure arises when the search algorithm is unable to find the global energy minimum corresponding to the crystal structure, a hard failure results from a flaw of the energy function to qualify the crystal structure as the predicted lowest energy conformation in docking simulations. We find that neither the determination of a single structure with the lowest energy nor finding the most common binding mode is sufficient to predict crystal structures of the complexes, which belong to the category of hard failures. In a proposed hierarchical approach, structural similarity clustering of the conformations, generated from equilibrium simulations with the simplified energy function, is followed by energy refinement with the AMBER force field. This protocol, that involves a hierarchy of energy functions, resolves some common failures in ligand-protein docking and detects crystallographic binding modes that were not found during docking simulations.

1999

47. Computer simulations of ligand-protein binding with ensembles of protein conformations: A Monte Carlo study of HIV-1 protease binding energy landscapes.
    Bouzida D, Rejto P. A, Arthurs S, Colson A. B, Freer S. T, Gehlhaar D. K, Larson V, Luty B. A, Rose P. W, Verkhivker G. International Journal of Quantum Chemistry. 1999, 72(1):73-84. DOI: 10.1002/(sici)1097-461x(1999)72:1<73::aid-qua7>3.0.co;2-o
48. Examining ligand-protein interactions with binding-energy landscapes.
    Rejto P. A, Bouzida D, Verkhivker G. Theoretical Chemistry Accounts. 1999, 131,148-152. doi: 10.1007/s002140050420
    Abstract

    Binding-energy landscapes are used to investigate the thermodynamics of molecular recognition for the pteridine ring, a recognition anchor in binding with dihydrofolate reductase, and two molecules with the same shape but different heteroatom substitutions. The relative importance of hydrogen bonding and hydrophobic interactions in this system is analyzed by comparing these three different decorations of the pteridine scaffold.
49. Monte Carlo study of ligand-protein binding energy landscapes with the weighted histogram analysis method.
    Bouzida D, Rejto P. A, Verkhivker G. International Journal of Quantum Chemistry. 1999. DOI: 10.1002/(sici)1097-461x(1999)73:2<113::aid-qua6>3.0.co;2-9
    Abstract

    The thermodynamics of molecular recognition is investigated by a statistical energy landscape approach, where the temperature profile of the ligand–protein binding process is determined using the weighted histogram analysis method. The analysis reveals differences in the binding energy landscapes of two molecular fragments with the FKBP12 protein, which are reflected in their characteristic transition temperatures. The approach provides insight into the nature of transitions between unbound and bound phases of ligand–protein complexes. One molecular fragment proceeds from the unbound phase to the native complex via a short-lived intermediate at relatively high temperature. The second fragment has a significantly more rugged binding energy landscape and goes from unbound to a long-lived nonspecific bound species consisting of isoenergetic yet structurally different binding modes, and later via a second-order-like transition to the native complex. Emerging universalities in molecular recognition and protein folding mechanisms are highlighted in the context of the kinetic partitioning mechanism.
50. Novel ATP-site cyclin-dependent kinase (CDK) inhibitors: Selective CDK inhibitors.
    Duvadie R. K, Chong W. K. M, Li L, Chu S. S, Yang Y. M, Nonomiya J, Tucker K. D, Lewis C. T, Knighton D. R, Ferre R. A. et al. Abstracts of Papers of the American Chemical Society. 1999. WOSUID: WOS:000082033902962
51. Thermodynamics and kinetics of ligand-protein binding studied with the weighted histogram analysis method and simulated annealing.
    Bouzida D, Arthurs S, Colson A.B, Freer S.T, Gehlhaar D.K, Larson V, Luty B.A, Rejto P.A, Rose P.W, Verkhivker G. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 1999. EID: 2-s2.0-0032610861
    Abstract

    The thermodynamics of ligand-protein molecular recognition is investigated by the energy landscape approach for two systems: methotrexate(MTX)–dihydrofolate reductase(DHFR) and biotin-streptavidin. The temperature-dependent binding free energy profile is determined using the weighted histogram analysis method. Two different force fields are employed in this study: a simplified model of ligand-protein interactions and the AMBER force field with a soft core smoothing component, used to soften the repulsive part of the potential. The results of multiple docking simulations are rationalized from the shape of the binding free energy profile that characterizes the thermodynamics of the binding process.
52. Towards understanding the mechanisms of molecular recognition by computer simulations of ligand-protein interactions.
    Verkhivker G. M, Rejto P. A, Bouzida D, Arthurs S, Colson A. B, Freer S. T, Gehlhaar D. K, Larson V, Luty B. A, Marrone T. et al. Journal of Molecular Recognition. 1999. DOI: 10.1002/(sici)1099-1352(199911/12)12:6<371::aid-jmr479>3.0.co;2-o
    Abstract

    The thermodynamic and kinetic aspects of molecular recognition for the methotrexate (MTX)–dihydrofolate reductase (DHFR) ligand–protein system are investigated by the binding energy landscape approach. The impact of ‘hot’ and ‘cold’ errors in ligand mutations on the thermodynamic stability of the native MTX–DHFR complex is analyzed, and relationships between the molecular recognition mechanism and the degree of ligand optimization are discussed. The nature and relative stability of intermediates and thermodynamic phases on the ligand–protein association pathway are studied, providing new insights into connections between protein folding and molecular recognition mechanisms, and cooperativity of ligand–protein binding. The results of kinetic docking simulations are rationalized based on the thermodynamic properties determined from equilibrium simulations and the shape of the underlying binding energy landscape. We show how evolutionary ligand selection for a receptor active site can produce well-optimized ligand–protein systems such as MTX–DHFR complex with the thermodynamically stable native structure and a direct transition mechanism of binding from unbound conformations to the unique native structure.
53. Unique cyclin-dependent kinase (CDK) inhibitors at the ATP-site.
    Chong W. K. M, Li L, Duvadie R. K, Chu S. S, Yang Y. M, Nonomiya J, Tucker K. D, Knighton D. R, Ferre R. A, Lundgren K. et al. Abstracts of Papers of the American Chemical Society. 1999. WOSUID: WOS:000082033903061
54. Thermodynamics and kinetics of ligand-protein binding studied with the weighted histogram analysis method and simulated annealing.
    Bouzida D, Arthurs S, Colson AB, Freer ST, Gehlhaar DK, Larson V, Luty BA, Rejto PA, Rose PW, Verkhivker G. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 1999, 426-37. doi: 10.1142/9789814447300_0042
    Abstract

    The thermodynamics of ligand-protein molecular recognition is investigated by the energy landscape approach for two systems: methotrexate(MTX)-dihydrofolate reductase(DHFR) and biotin-streptavidin. The temperature-dependent binding free energy profile is determined using the weighted histogram analysis method. Two different force fields are employed in this study: a simplified model of ligand-protein interactions and the AMBER force field with a soft core smoothing component, used to soften the repulsive part of the potential. The results of multiple docking simulations are rationalized from the shape of the binding free energy profile that characterizes the thermodynamics of the binding process.

1998

39. Ligand-protein binding energy landscapes in drug design.
    Rejto P. A, Bouzida D, Verkhivker G. Abstracts of Papers of the American Chemical Society. 1998. WOSUID: WOS:000075234902058
40. Molecular anchors with large stability gaps ensure linear binding free energy relationships for hydrophobic substituents.
    Rejto P.A, Verkhivker G. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 1998, 362-73. EID: 2-s2.0-0031635564
    Abstract

    Ligand-protein docking simulations are employed to analyze the binding energy landscape of the pipecolinyl fragment that serves as a recognition core of the FK506 ligand in binding with the FKBP12 protein. This fragment acts as a molecular anchor that specifically binds within the protein active site in a unique binding mode, in harmony with the structure of the FK506-FKBP12 complex. Molecular anchors are characterized by a large stability gap, defined to be the free energy of a ligand bound in the native binding mode relative to the free energy of alternative binding modes. For ligands that share a common anchor fragment, a linear binding free energy relationship may be expected for hydrophobic substituents provided they do not abrogate the anchor binding mode. Changes in solvent-accessible surface area for these peripheral groups are used to rationalize the relative binding affinities of a series of FKBP12-ligand complexes which share the pipecolinyl anchor fragment. A series of benzene derivatives that bind to a mutant form of T4 lysozyme is also analyzed, and implications for structure-based drug design are discussed.
41. Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization.
    Schaffer L, Verkhivker G. Proteins-Structure Function and Bioinformatics. 1998, 33, 2,295-310. doi: 10.1002/(sici)1097-0134(19981101)33:2<295::aid-prot12>3.0.co;2-f
    Abstract

    We present a computational approach for predicting structures of ligand-protein complexes and analyzing binding energy landscapes that combines Monte Carlo simulated annealing technique to determine the ligand bound conformation with the dead-end elimination algorithm for side-chain optimization of the protein active site residues. Flexible ligand docking and optimization of mobile protein side-chains have been performed to predict structural effects in the V32I/I47V/V82I HIV-1 protease mutant bound with the SB203386 ligand and in the V82A HIV-1 protease mutant bound with the A77003 ligand. The computational structure predictions are consistent with the crystal structures of these ligand-protein complexes. The emerging relationships between ligand docking and side-chain optimization of the active site residues are rationalized based on the analysis of the ligand-protein binding energy landscape.
42. Molecular anchors with large stability gaps ensure linear binding free energy relationships for hydrophobic substituents.
    Rejto PA, Verkhivker G. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 1998, 362-73.
    Abstract

    Ligand-protein docking simulations are employed to analyze the binding energy landscape of the pipecolinyl fragment that serves as a recognition core of the FK506 ligand in binding with the FKBP12 protein. This fragment acts as a molecular anchor that specifically binds within the protein active site in a unique binding mode, in harmony with the structure of the FK506-FKBP12 complex. Molecular anchors are characterized by a large stability gap, defined to be the free energy of a ligand bound in the native binding mode relative to the free energy of alternative binding modes. For ligands that share a common anchor fragment, a linear binding free energy relationship may be expected for hydrophobic substituents provided they do not abrogate the anchor binding mode. Changes in solvent-accessible surface area for these peripheral groups are used to rationalize the relative binding affinities of a series of FKBP12-ligand complexes which share the pipecolinyl anchor fragment. A series of benzene derivatives that bind to a mutant form of T4 lysozyme is also analyzed, and implications for structure-based drug design are discussed.

1997

35. Mean field analysis of FKBP12 complexes with FK506 and rapamycin: Implications for a role of crystallographic water molecules in molecular recognition and specificity.
    Rejto PA, Verkhivker G. Proteins-Structure Function and Genetics. 1997, 28,3,313-24. WOSUID: WOS:A1997XH81500002
    Abstract

    Mean field analysis of FKBP12 complexes with FK506 and rapamycin has been performed by using structures obtained from molecular docking simulations on a simple, yet robust molecular recognition energy landscape. When crystallographic water molecules are included in the simulations as an extension of the FKBP12 protein surface, there is an appreciable stability gap between the energy of the native FKBP12-FK506 complex and energies of conformations with the “native-like” binding mode. By contrast, the energy spectrum of the FKBP12-rapamycin complex is dense regardless of the presence of the water molecules. The stability gap in the FKBP12-FK506 system is determined by two critical water molecules from the effector region that participate in a network of specific hydrogen bond interactions. This interaction pattern protects the integrity and precision of the composite ligand-protein effector surface in the binary FKBP12-FK506 complex and is preserved in the crystal structure of the FKBP12-FK506-calcineurin ternary complex. These features of the binding energy landscapes provide useful insights into specific and nonspecific aspects of FK506 and rapamycin recognition.
36. Structural consensus in ligand-protein docking identifies recognition peptide motifs that bind streptavidin.
    Shah N.K, Rejto P.A, Verkhivker G. Proteins: Structure, Function and Genetics. 1997, 28,3,421-33. doi: 10.1002/(SICI)1097-0134(199707)28:3<421::AID-PROT11>3.0.CO;2-J
    Abstract

    Computational structure prediction of streptavidin-peptide complexes for known recognition sequences and a number of random di-, tri-, and tetrapeptides has been conducted, and mechanisms of peptide recognition with streptavidin have been investigated by a new computational protocol. The structural consensus criterion, which is computed from multiple docking simulations and measures the accessibility of the dominant binding mode, identifies recognition motifs from a set of random peptide sequences, whereas energetic analysis is less discriminatory. The predicted conformations of recognition tripeptide and tetrapeptide sequences are also in structural harmony and composed of peptide fragments that are individually unfrustrated in their bound conformation, resulting in a minimally frustrated energy landscape for recognition peptides.

1996

33. A mean field model of ligand protein interactions: Implications for the structural assessment of human immunodeficiency virus type 1 protease complexes and receptor-specific binding.
    Verkhivker G, Rejto P. Proceedings of the National Academy of Sciences of the United States of America. 1996. doi: 10.1073/pnas.93.1.60
    Abstract

    We propose a general mean field model of ligand-protein interactions to determine the thermodynamic equilibrium of a system at finite temperature. The method is employed in structural assessments of two human immuno-deficiency virus type 1 protease complexes where the gross effects of protein flexibility are incorporated by utilizing a data base of crystal structures. Analysis of the energy spectra for these complexes has revealed that structural and thermo-dynamic aspects of molecular recognition can be rationalized on the basis of the extent of frustration in the binding energy landscape. In particular, the relationship between receptor-specific binding of these ligands to human immunodeficiency virus type 1 protease and a minimal frustration principle is analyzed.
34. Empirical free energy calculations of human immunodeficiency virus type 1 protease crystallographic complexes. II. Knowledge-based ligand-protein interaction potentials applied to thermodynamic analysis of hydrophobic mutations.
    Verkhivker G. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 1996, 638-52. EID: 2-s2.0-0030309963
    Abstract

    Empirical free energy calculations of HIV-1 protease crystallographic complexes based on the developed knowledge-based ligand-protein interaction potentials have enabled a detailed thermodynamic analysis. Binding free energies are estimated within an empirical model that postulates that hydrophobic effect, mean field ligand-protein interaction potentials and conformational entropy changes are the dominant forces that determine complex formation. To provide a quantitative framework of the binding thermodynamics contributions the derived knowledge-based potentials have been linked with the hydrophobicity and conformational entropy scales originally developed to explain protein stability. The comparative analysis of studied inhibitors provides reasonable estimates of distinctions in their binding affinity with HIV-1 protease and gives insight into the nature of the binding determinants. The binding free energy changes upon a simple hydrophobic mutation Ile -> Val in the JG-365, MVT-101 and U75875 inhibitors of HIV-1 protease have been evaluated within a model that includes the effects of solvation, cavity formation, conformational entropy and mean field ligand-protein interactions. In general, free energy changes associated with a particular perturbation of a system can not be rigorously decomposed into separate terms from first principles. We explored the relationships between the changes in hydrophobic contributions and mean field ligand-protein interaction energies in the context of a totally buried and dense area of the binding site. We assume, therefore, that these simple hydrophobic deletions would not induce noticeable conformational changes in the enzyme and can be interpreted with some confidence in the framework of the model. The analysis has revealed the decisive effect of the energetics of ligand-protein interactions on the estimated free energy changes.
35. Exploring the energy landscapes of molecular recognition by a genetic algorithm: Analysis of the requirements for robust docking of HIV-1 protease and FKRP-12 complexes.
    Verkhivker G, Rejto P. A, Gehlhaar D. K, Freer S. T. Proteins-Structure Function and Genetics. 1996. DOI: 10.1002/(sici)1097-0134(199607)25:3<342::aid-prot6>3.3.co;2-3
36. Unraveling principles of lead discovery: From unfrustrated energy landscapes to novel molecular anchors.
    Rejto P. A, Verkhivker G. Proceedings of the National Academy of Sciences of the United States of America. 1996, 93(17):8945-50. DOI: 10.1073/pnas.93.17.8945
    Abstract

    The search for novel leads is a critical step in the drug discovery process. Computational approaches to identify new lead molecules have focused on discovering complete ligands by evaluating the binding affinity of a large number of candidates, a task of considerable complexity. A new computational method is introduced in this work based on the premise that the primary molecular recognition event in the protein binding site may be accomplished by small core fragments that serve as molecular anchors, providing a structurally stable platform that can be subsequently tailored into complete ligands. To fulfill its role, we show that an effective molecular anchor must meet both the thermodynamic requirement of relative energetic stability of a single binding mode and its consistent kinetic accessibility, which may be measured by the structural consensus of multiple docking simulations. From a large number of candidates, this technique is able to identify known core fragments responsible for primary recognition by the FK506 binding protein (FKBP-12), along with a diverse repertoire of novel molecular cores. By contrast, absolute energetic criteria for selecting molecular anchors are found to be promiscuous. A relationship between a minimum frustration principle of binding energy landscapes and receptor-specific molecular anchors in their role as “recognition nuclei” is established, thereby unraveling a mechanism of lead discovery and providing a practical route to receptor-biased computational combinatorial chemistry.
37. Exploring the energy landscapes of molecular recognition by a genetic algorithm: analysis of the requirements for robust docking of HIV-1 protease and FKBP-12 complexes.
    Verkhivker G, Rejto PA, Gehlhaar DK, Freer ST. Proteins. 1996, 25,3,342-53. doi: 10.1002/(sici)1097-0134(199607)25:3<342::aid-prot6>3.0.co;2-h
    Abstract

    Energy landscapes of molecular recognition are explored by performing “semi-rigid” docking of FK-506 and rapamycin with the Fukisawa binding protein (FKBP-12), and flexible docking simulations of the Ro-31-8959 and AG-1284 inhibitors with HIV-1 protease by a genetic algorithm. The requirements of a molecular recognition model to meet thermodynamic and kinetic criteria of ligand-protein docking simultaneously are investigated using a family of simple molecular recognition energy functions. The critical factor that determines the success rate in predicting the structure of ligand-protein complexes is found to be the roughness of the binding energy landscape, in accordance with a minimal frustration principle. The results suggest that further progress in structure prediction of ligand-protein complexes can be achieved by designing molecular recognition energy functions that generate binding landscapes with reduced frustration.
38. Empirical free energy calculations of human immunodeficiency virus type 1 protease crystallographic complexes. II. Knowledge-based ligand-protein interaction potentials applied to thermodynamic analysis of hydrophobic mutations.
    Verkhivker G. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 1996, 638-52.
    Abstract

    Empirical free energy calculations of HIV-1 protease crystallographic complexes based on the developed knowledge-based ligand-protein interaction potentials have enabled a detailed thermodynamic analysis. Binding free energies are estimated within an empirical model that postulates that hydrophobic effect, mean field ligand-protein interaction potentials and conformational entropy changes are the dominant forces that determine complex formation. To provide a quantitative framework of the binding thermodynamics contributions the derived knowledge-based potentials have been linked with the hydrophobicity and conformational entropy scales originally developed to explain protein stability. The comparative analysis of studied inhibitors provides reasonable estimates of distinctions in their binding affinity with HIV-1 protease and gives insight into the nature of the binding determinants. The binding free energy changes upon a simple hydrophobic mutation Ile -> Val in the JG-365, MVT-101 and U75875 inhibitors of HIV-1 protease have been evaluated within a model that includes the effects of solvation, cavity formation, conformational entropy and mean field ligand-protein interactions. In general, free energy changes associated with a particular perturbation of a system can not be rigorously decomposed into separate terms from first principles. We explored the relationships between the changes in hydrophobic contributions and mean field ligand-protein interaction energies in the context of a totally buried and dense area of the binding site. We assume, therefore, that these simple hydrophobic deletions would not induce noticeable conformational changes in the enzyme and can be interpreted with some confidence in the framework of the model. The analysis has revealed the decisive effect of the energetics of ligand-protein interactions on the estimated free energy changes.

1995

27. Computer-aided structure prediction of ligand-protein complexes: Exploring the energy landscapes of molecular recognition with HIV-1 protease.
    Verkhivker G, Rejto P.A, Gehlhaar D.K, Freer S.T. International Antiviral News. 1995, 3,146-147. EID: 2-s2.0-0028823563
28. DOCKING CONFORMATIONALLY FLEXIBLE SMALL MOLECULES INTO A PROTEIN-BINDING SITE THROUGH SIMULATED EVOLUTION.
    Gehlhaar D. K, Verkhivker G, Freer S. T. Abstracts of Papers of the American Chemical Society. 1995, p.615-627. 615-627p. WOSUID: WOS:A1995QP23201907
29. EMPIRICAL FREE-ENERGY CALCULATIONS OF LIGAND-PROTEIN CRYSTALLOGRAPHIC COMPLEXES .1. KNOWLEDGE-BASED LIGAND-PROTEIN INTERACTION POTENTIALS APPLIED TO THE PREDICTION OF HUMAN-IMMUNODEFICIENCY-VIRUS-1 PROTEASE BINDING-AFFINITY.
    Verkhivker G, Appelt K, Freer S. T, Villafranca J. E. Protein Engineering. 1995, Chapter 85, p.261-265. 261-265p. doi: 10.1093/protein/8.7.677
    Abstract

    The steadily increasing number of high-resolution human immunodeficiency virus (HIV) 1 protease complexes has been the impetus for the elaboration of knowledge-based mean field ligand-protein interaction potentials. These potentials have been linked with the hydrophobicity and conformational entropy scales developed originally to explain protein folding and stability. Empirical free energy calculations of a diverse set of HIV-1 protease crystallographic complexes have enabled a detailed analysis of binding thermodynamics. The thermodynamic consequences of conformational changes that HIV-1 protease undergoes upon binding to all inhibitors, and a substantial concomitant loss of conformational entropy by the part of HIV-1 protease that forms the ligand-protein interface, have been examined. The quantitative breakdown of the entropy-driven changes occurring during ligand-protein association, such as the hydrophobic contribution, the conformational entropy term and the entropy loss due to a reduction of rotational and translationsal degrees of freedom, of a system composed of ligand, protein and crystallographic water molecules at the ligand-protein interface has been carried out The proposed approach provides reasonable estimates of distinctions in binding affinity and gives an insight into the nature of enthalpy-entropy compensation factors detected in the binding process.
30. MOIL – A PROGRAM FOR SIMULATIONS OF MACROMOLECULES
    Elber R, Roitberg A, Simmerling C, Goldstein R, Li H. Y, Verkhivker G, Keasar C, Zhang J, Ulitsky A. Computer Physics Communications. 1995, p.165-191.165-191p. doi: 10.1016/0010-4655(95)00047-j
    Abstract

    A package of computer programs for molecular dynamics simulations-MOIL-is described. A flexible data structure enables the study of macromolecules with potentials consistent with the AMBER/OPLS force field. The supplied parameter set has proteins in mind. In addition to ‘wide spread’ applications such as energy, energy minimization, normal modes, dynamics and free energy calculations code is also provided to pursue less common applications. This includes reaction path calculations (in condensed phases), uses of the mean field approach for enhanced sampling (LES-locally enhanced sampling) and calculations of curve crossing using the Landau-Zener model. A brief review of the overall program is provided. A few modules are discussed in considerable detail.
31. MOLECULAR RECOGNITION OF THE INHIBITOR AG-1343 BY HIV-1 PROTEASE – CONFORMATIONALLY FLEXIBLE DOCKING BY EVOLUTIONARY PROGRAMMING.
    Gehlhaar D. K, Verkhivker G, Rejto P. A, Sherman C. J, Fogel D. B, Fogel L. J, Freer S. T. Chemistry & Biology. 1995. DOI: 10.1016/1074-5521(95)90050-0

1993

22. FREE-ENERGY SIMULATIONS OF THE PROTEIN LEGHEMOGLOBIN MUTANTS – MEAN-FIELD STUDIES OF THE NATIVE-STATE STABILITY AND LIGAND DIFFUSION.
    Verkhivker G, Elber R. Abstracts of Papers of the American Chemical Society. 1993. WOSUID: WOS:A1993LP32101320
23. FREE-ENERGY SIMULATIONS OF THE PROTEIN LEGHEMOGLOBIN MUTANTS – MOLECULAR-DYNAMICS AND MEAN-FIELD STUDIES OF THE FOLDED STATE STABILITY.
    Verkhivker G, Elber R. Abstracts of Papers of the American Chemical Society. 1993. WOSUID: WOS:A1993LP32200871

1992

20. LOCALLY ENHANCED SAMPLING IN FREE-ENERGY CALCULATIONS – APPLICATION OF MEAN FIELD APPROXIMATION TO ACCURATE CALCULATION OF FREE-ENERGY DIFFERENCES.
    Verkhivker G, Elber R, Nowak W. Journal of Chemical Physics. 1992. DOI: 10.1063/1.463456
    Abstract

    Mean field approximation is employed for accurate calculation of free energy differences. Significantly enhanced sampling is obtained for local changes. In an example for the mutation of a residue in a protein, the increase in the sampling yielded converged results at a significantly lower computational cost than the usual approach.
21. MICROSCOPIC MODELING OF LIGAND DIFFUSION THROUGH A PROTEIN – CARBON-MONOXIDE IN LEGHEMOGLOBIN.
    Verkhivker G, Elber R. Abstracts of Papers of the American Chemical Society. 1992. WOSUID: WOS:A1992JJ31300920
22. MICROSCOPIC MODELING OF LIGAND DIFFUSION THROUGH A PROTEIN – CARBON-MONOXIDE IN LEGHEMOGLOBIN.
    Verkhivker G, Elber R. Abstracts of Papers of the American Chemical Society. 1992. WOSUID: WOS:A1992JJ31300920
23. MICROSCOPIC MODELING OF LIGAND DIFFUSION THROUGH THE PROTEIN LEGHEMOGLOBIN – COMPUTER-SIMULATIONS AND EXPERIMENTS.
    Verkhivker G, Elber R, Gibson Q H. Journal of the American Chemical Society. 1992. DOI: 10.1021/ja00046a036

1990

16. ANALYSIS OF COMPLEXATING ABILITY OF 12-CROWN-4 BY THE MOLECULAR ELECTROSTATIC POTENTIAL METHOD.
    Kuzmin V. E, Rublev I. S, Korovin S. V, Verkhivker G. Ukrainskii Khimicheskii Zhurnal. 1990. WOSUID: WOS:A1990CT29300019
17. ANALYSIS OF THE COMPLEXING ABILITY OF 18-CROWN-6 BY THE METHOD OF MOLECULAR ELECTROSTATIC POTENTIAL.
    Kuzmin V. E, Rublev I. S, Verkhivker G, Korovin S.V. Ukrainskii Khimicheskii Zhurnal. 1990. WOSUID: WOS:A1990CY50700026

1989

14. CONFORMATIONAL FACTORS OF THE ISOTOPIC SELECTIVITY OF 18-CROWN-6.
    Verkhivker G, Kuzmin V. E. Dopovidi Akademii Nauk Ukrainskoi Rsr Seriya B-Geologichni Khimichni Ta Biologichni Nauki. 1989. WOSUID: WOS:A1989T236100009
15. CONFORMATIONAL FACTORS OF THE ISOTOPIC SELECTIVITY OF 18-CROWN-6.
    Khutorskii V.E, Kamenchuk A.A, Verkhivker G.M, Kuz’min V.E. Dopovidi Akademii Nauk Ukrainskoi Rsr Seriya B-Geologichni Khimichni Ta Biologichni Nauki. 1989. WOSUID: WOS:A1989T236100009
16. Contribution from the aqueous phase to stability of Cs⁺ and Na⁺ cryptand[2.2.2] complexes.
    Khutorskii V.E, Kamenchuk A.A, Verkhivker G, Kuz’min V.E. Theoretical and Experimental Chemistry. 1989. DOI: 10.1007/BF00534459
17. CONTRIBUTION OF AQUEOUS PHASE TO STABILITY OF THE COMPLEXES OF CRYPTAND 2.2.2 WITH CS+ AND NA+.
    Khutorskii V.E, Kamenchuk A.A, Verkhivker G, Kuz’min V.E. Teoreticheskaya I Eksperimentalnaya Khimiya. 1989. WOSUID: WOS:A1989CT58500024

1988

10. Gas power plants in the power system.
    Verkhivker G, Pflugbail’ I, Yantovskii E.I. Thermal Engineering (English translation of Teploenergetika). 1988. EID: 2-s2.0-0024096910
11. GAS POWER-PLANTS IN THE POWER-SYSTEM.
    Verkhivker G, Pflugbail’ I, Yantovskii E.I. Thermal Engineering. 1988. WOSUID: WOS:A1988U948100010
12. THEORETICAL CONFORMATION ANALYSIS OF THE KINETIC MACROCYCLIC EFFECT.
    Kuzmin V. E, Verkhivker G. Dopovidi Akademii Nauk Ukrainskoi Rsr Seriya B-Geologichni Khimichni Ta Biologichni Nauki. 1988. WOSUID: WOS:A1988R303500013

1987

7. NUCLEAR/GAS POWER PLANT.
   Verkhivker G, Yantovskii E.I. Thermal Engineering (English translation of Teploenergetika).1987. EID: 2-s2.0-0023451440

1985

6. A NUMERICAL-METHOD OF SEARCH FOR THE REACTION-PATH AND SADDLE-POINT ON A POTENTIAL SURFACE – APPLICATION TO THE CONFORMATIONAL ISOMERIZATION OF CYCLOHEXANE.
   Dashevskii V. G, Verkhivker G, Kuzmin V. E. Doklady Akademii Nauk Sssr. 1985. WOSUID: WOS:A1985AFE4600026
7. A POSSIBLE APPROACH TO DETERMINATION OF THE PREFERRED CONFORMATIONS IN SUBSTITUTED SATURATED 7-MEMBERED RINGS.
   Kuzmin V. E, Kamalov G. L, Verkhivker G. Journal of Structural Chemistry. 1985. WOSUID: WOS:A1985C717200002
8. A possible approach to determination of the preferred conformations in substituted saturated seven-membered rings.
   Kuzmin V. E, Kamalov G. L, Verkhivker G. Journal of Structural Chemistry. 1985. DOI: 10.1007/BF00754118

1984

3. NUCLEAR GAS POWER-PLANT.
   Verkhivker G. P, Yantovskii E. I. Thermal Engineering. 1984. WOSUID: WOS:A1984ALS3600002

1981

2. METHOD FOR COMPARING NUCLEAR-POWER AND PRODUCTION PROCESS INSTALLATIONS.
   Verkhivker G, Kravchenko V. P. Soviet Atomic Energy. 1981. DOI: 10.1007/bf01126342
3. The predominant conformation of 1,3-dioxepane.
   Kamalov G.L, Kuz’min V.E, Sharygin V.N, Verkhivker G. Theoretical and Experimental Chemistry. 1981. DOI: 10.1007/BF01114439