Biology subjects

Verkhivker, G.

Publications and source records attributed to Verkhivker, G..

6 recordsLinked to original sources

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↗