scholarly journals Mutation-Induced Long-Range Allosteric Interactions in the Spike Protein Determine the Infectivity of SARS-CoV-2 Emerging Variants

ACS Omega ◽  
2021 ◽  
Author(s):  
Jayanta Kumar Das ◽  
Bikash Thakuri ◽  
Krishnan MohanKumar ◽  
Swarup Roy ◽  
Adnan Sljoka ◽  
...  
Keyword(s):  
Long Range ◽  
Spike Protein ◽  
Allosteric Interactions

scholarly journals 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

2021 ◽  
Author(s):  
Gennady M. Verkhivker ◽  
Luisa Di Paola
Keyword(s):  
Structural Changes ◽  
Molecular Mechanisms ◽  
Specific Binding ◽  
Network Modeling ◽  
Signal Propagation ◽  
Spike Protein ◽  
Hierarchical Network ◽  
Functional Regions ◽  
Allosteric Interactions ◽  
Spike Proteins

AbstractThe 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.

scholarly journals Formins Regulate Actin Filament Flexibility through Long Range Allosteric Interactions

2006 ◽  
Vol 281 (16) ◽  
pp. 10727-10736 ◽  
Author(s):  
Beáta Bugyi ◽  
Gábor Papp ◽  
Gábor Hild ◽  
Dénes Lôrinczy ◽  
Elisa M. Nevalainen ◽  
...  
Keyword(s):  
Long Range ◽  
Actin Filament ◽  
Allosteric Interactions

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

2021 ◽  
Author(s):  
Gennady Verkhivker
Keyword(s):  
Protein Binding ◽  
Long Range ◽  
Binding Free Energy ◽  
Spike Protein ◽  
Neutralizing Capacity ◽  
Binding Epitope ◽  
Escape Mutants ◽  
Centrality Analysis ◽  
Communication Paths ◽  
Structurally Stable

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.

scholarly journals Long-Range Allosteric Interactions between the Folate and Methionine Cycles Stabilize DNA Methylation Reaction Rate

Epigenetics ◽  
2006 ◽  
Vol 1 (2) ◽  
pp. 81-87 ◽  
Author(s):  
H.Frederik Nijhout ◽  
Michael C. Reed ◽  
David F. Anderson ◽  
Jonathan C. Mattingly ◽  
S. Jill James ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Long Range ◽  
Reaction Rate ◽  
Methylation Reaction ◽  
Allosteric Interactions

scholarly journals 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

2021 ◽  
Author(s):  
Gennady M. Verkhivker ◽  
Steve Agajanian ◽  
Deniz Yazar Oztas ◽  
Grace Gupta
Keyword(s):  
Neutralizing Antibodies ◽  
Molecular Mechanisms ◽  
Protein Complexes ◽  
Community Analysis ◽  
Significant Degree ◽  
Spike Protein ◽  
Alanine Scanning ◽  
Allosteric Interactions ◽  
Allosteric Communication ◽  
Functional Dynamics

AbstractIn 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.

scholarly journals Elastic Network Modeling of Cellular Networks Unveils Sensor and Effector Genes that Control Information Flow

2021 ◽  
Author(s):  
Omer Acar ◽  
She Zhang ◽  
Ivet Bahar ◽  
Anne-Ruxandra Carvunis
Keyword(s):  
Cellular Networks ◽  
Long Range ◽  
Network Modeling ◽  
Genetic Network ◽  
Elastic Network Model ◽  
Elastic Network ◽  
Cellular Processes ◽  
Allosteric Interactions ◽  
Long Range Interactions ◽  
High Level

The high-level organization of the cell is embedded in long-range interactions that connect distinct cellular processes. Existing approaches for detecting long-range interactions consist of propagating information from source nodes through cellular networks, but the selection of source nodes is inherently biased by prior knowledge. Here, we sought to derive an unbiased view of long-range interactions by adapting a perturbation-response scanning strategy initially developed for identifying allosteric interactions within proteins. We deployed this strategy onto an elastic network model of the yeast genetic network. The genetic network revealed a superior propensity for long-range interactions relative to simulated networks with similar topology. Long-range interactions were detected systematically throughout the network and found to be enriched in specific biological processes. Furthermore, perturbation-response scanning identified the major sources and receivers of information in the network, named effector and sensor genes, respectively. Effectors formed dense clusters centrally integrated into the network, whereas sensors formed loosely connected antenna-shaped clusters. Long-range interactions between effector and sensor clusters represent the major paths of information in the network. Our results demonstrate that elastic network modeling of cellular networks constitutes a promising strategy to probe the high-level organization of the cell.

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