Biology subjects

Verkhivker, G.

Publications and source records attributed to Verkhivker, G..

48 records · Page 3Linked to original sources

bioRxiv2022

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

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 local and global effects of mutations in the complexes, identify structural 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 structural stability signatures of the spike complexes that can dictate the pattern of mutational escape. By employing an integrated analysis of conformational dynamics and binding energetics, we found that the potent antibodies that efficiently neutralize Omicron spike variant can form the dominant binding energy hotpots with the conserved stability centers in which mutations may be restricted by the requirements of the folding stability and binding to the host receptor. The results show that protein stability and binding energetics of the SARS-CoV-2 spike complexes with the panel of cross-reactive ultrapotent antibodies are tolerant to the constellation of Omicron mutations. A network-based perturbation approach for mutational profiling of allosteric residues potentials revealed how antibody binding can modulate allosteric interactions and identified allosteric control points that can form vulnerable sites for mutational escape. This study suggested a mechanism in which the pattern of specific escape mutants for ultrapotent antibodies may not be solely determined by the binding interaction changes but are driven by a complex balance and tradeoffs between different local and global factors including the impact of mutations on structural stability, binding strength, long-range interactions and fidelity of allosteric signaling.

biophysics↗

bioRxiv2022

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

Understanding 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 cochaperone and client protein 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 hotspots of protein stability and binding affinity in the Hsp90 complexes, showing that binding hotspots 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 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 allosteric interactions and long-range communications required for client remodeling and activation.

biophysics↗

bioRxiv2022

Dissecting Mutational Allosteric Effects in Alkaline Phosphatases Associated with Different Hypophosphatasia Phenotypes: An Integrative Computational Investigation

Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization, 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 for large-scale analysis of ALPL mutations - from nonpathogenic to severe HPPs is proposed. Allosteric molecular signatures of ALPL mutations were determined using an integrated pipeline of synergistic approaches including sequence and energetic-based analysis, structural topology network modeling and elastic network models. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control and mild and severe HPP phenotypes, and the developed machine learning model suggested that the topological network parameters could serve as is a robust indicator for severe mutations. Molecular dynamics simulations coupled with protein structure network was employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and we found that severe disease-associated mutations have a significantly greater effect on allosteric communications. The results of this study suggested that ALPL mutations associated with mild and severe HPPs tend to have different effects on protein stability on local scale and long-range communications caused by network rewiring. By linking disease phenotypes with allosteric molecular signatures, the proposed integrative computational approach elucidates the complex sequence-structure-allostery relationships of ALPL mutations and dissects the role of allosteric effects in the pathogenesis of HPPs. Author SummaryThe understanding of mutational genotype- disease phenotype relationship is a fundamental step for enabling precision medicine. It remains a challenging task to assess the molecular principle of the genotype- phenotype relationship. By focusing on Hypophosphatasia, a rare inherited disorder, as an example, we performed comprehensive analysis of single-amino-acid mutations in the encoded protein of Tissue Nonspecific Alkaline Phosphatase associated in terms of their sequence, structure, and dynamics properties. We further developed a machine learning -based method to classify different disease phenotypes, and the interpretability of the classification model was addressed by the structural-functional analysis of network topological important mutations. Our results highlighted the allosteric propensity of severe mutations, and show the potential allosteric principle of genotype- phenotype relationship.

biophysics↗

bioRxiv2021

Allosteric Determinants of the SARS-CoV-2 Spike Protein Binding with Nanobodies: Examining Mechanisms of Mutational Escape and Sensitivity of the Omicron Variant

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 study, we performed a comprehensive computational analysis of the SARS-CoV-2 spike trimer complexes with Nb6, VHH E and bi-paratopic VHH VE nanobodies. We combined atomistic dynamics and collective motions 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 may exploit 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 VE 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.

biophysics↗

bioRxiv2021

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

The experimental and computational studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across variants of concern(VOCs), linking the effect of this mutation with the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies characterized the closed and open states of the B.1.1.7 (B.1.1.7) and B.1.351 (Beta) spike variants allowing for a more detailed atomistic characterization of the conformational landscapes and functional changes. In this study, we employed coarse-grained simulations of the SARS-CoV-2 spike variant trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration analysis of the conformational ensembles with collective dynamics and residue-based mutational scanning of protein stability, we determine protein stability hotspots and identify potential energetic drivers favoring the receptor-accessible open spike states for the B.1.1.7 and B.1.351 spike variants. Through mutational scanning of protein stability changes we quantify mutational adaptability of the S-G614, S-B.1.1.7 and S-B.1.351 variants in different functional forms. Using this analysis, we found a significant conformational and mutational plasticity of the open states for all studied variants. The results of this study suggest that modulation of the energetic frustration at the inter-protomer interfaces can serve as a mechanism for allosteric couplings between mutational sites, the inter-protomer hinges of functional motions and motions of the receptor-binding domain required for binding of the host cell receptor. The proposed mechanism of mutation-induced energetic frustration may result in the greater adaptability and the emergence of multiple conformational substates in the open form. This study also suggested functional relationships between mutation-induced modulation of protein dynamics, local frustration and allosteric regulation of the SARS-CoV-2 spike protein.

biophysics↗

bioRxiv2021

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

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.

biophysics↗

bioRxiv2021

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

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.

biophysics↗

bioRxiv2021

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

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.

biophysics↗

bioRxiv2021

Landscape-Based Mutational Sensitivity Cartography and Network Community Analysis of the SARS-CoV-2 Spike Protein Structures: Quantifying Functional Effects of the Circulating Variants

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. 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 atomistic simulations, deep mutational scanning and sensitivity mapping together with the network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Conformational dynamics and analysis of collective motions in the SARS-CoV-2 spike proteins demonstrated that the D614 position anchors a key regulatory cluster that dictates functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of the spike residues, we identified the evolution of stability hotspots in the SARS-CoV-2 spike structures of the mutant trimers. The results offer support to the reduced shedding mechanism of as a driver of the increased infectivity triggered by the D614G mutation. By employing the landscape-based 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 in the open form by enhancing the stability of the inter-domain interactions. This study provides atomistic view of the interactions and stability hotspots in the SARS-CoV-2 spike proteins, offering a useful insight into the molecular mechanisms of the D614G mutation that can exert its functional effects through allosterically induced changes on stability of the residue interaction networks.

biophysics↗

bioRxiv2021

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

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.

biophysics↗

bioRxiv2021

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

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.

biophysics↗

bioRxiv2021

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

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.

biophysics↗