G. Verkhivker

Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations

This study uses AlphaFold2 and molecular dynamics to predict conformational ensembles and binding mechanisms of SARS-CoV-2 Omicron variants, showing agreement with experimental data.

Interpretable Atomistic Prediction and Functional Analysis of Conformational Ensembles and Allosteric States in Protein Kinases Using AlphaFold2 Adaptation with Randomized Sequence Scanning and Local Frustration Profiling

This study adapts AlphaFold2 to predict conformational ensembles and allosteric states of ABL kinase using sequence scanning and frustration profiling, revealing limitations in detecting low-populated inactive states.

Microsecond Molecular Dynamics Simulations and Markov State Models of Mutation-Induced Allosteric Mechanisms for the Light-Oxygen-Voltage 2 Protein : Revealing Structural Basis of Signal Transmission Induced by Photoactivation of the Light Protein State

This study uses molecular dynamics simulations and Markov state models to analyze mutation-induced allostery in AsLOV2, identifying key β-sheet interactions critical for signal transmission during photoactivation.

AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance

This study uses AlphaFold2 and molecular simulations to analyze how mutations in SARS-CoV-2 Spike protein variants balance ACE2 binding and antibody resistance through epistatic interactions.

Accurate Characterization of Conformational Ensembles and Binding Mechanisms of the SARS-CoV-2 Omicron BA.2 and BA.2.86 Spike Protein with the Host Receptor and Distinct Classes of Antibodies Using AlphaFold2-Augmented Integrative Computational Modeling

This study uses AlphaFold2 and molecular dynamics to analyze the structure, dynamics, and binding of SARS-CoV-2 Omicron BA.2.86 spike protein with ACE2 and antibodies, revealing key mutations that enhance immune evasion and ACE2 binding.

Examining Functional Linkages Between Conformational Dynamics, Protein Stability and Evolution of Cryptic Binding Pockets in the SARS-CoV-2 Omicron Spike Complexes with the ACE2 Host Receptor: Recombinant Omicron Variants Mediate Variability of Conserved Allosteric Sites and Binding Epitopes

This study uses simulations and analysis of SARS-CoV-2 Omicron variants to examine conformational dynamics, protein stability, and evolution of cryptic binding pockets in the spike complex with ACE2.

Ensemble-Based Modeling of the SARS-CoV-2 Omicron BA.1 and BA.2 Spike Trimers and Systematic Characterization of Cryptic Binding Pockets in Distinct Functional States : Emergence of Conformation-Sensitive and Variant-Specific Allosteric Binding Sites

Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variants Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms

This study uses computational methods to analyze conformational dynamics and allosteric pockets in SARS-CoV-2 Omicron variants bound to ACE2, revealing how convergent mutations influence immune escape and functional mechanisms.

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

This study uses simulations and profiling to analyze how Omicron mutations affect binding, allostery, and thermodynamics in SARS-CoV-2 complexes with ACE2.

Balancing Functional Tradeoffs between Protein Stability and ACE2 Binding in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB Lineages : Dynamics-Based Network Models Reveal Epistatic Effects Modulating Compensatory Dynamic and Energetic Changes

This study uses computational models to analyze how mutations in SARS-CoV-2 Omicron variants balance protein stability and ACE2 binding through epistatic interactions and dynamic changes.

Coarse-Grained Molecular Simulations and Ensemble-Based Mutational Profiling of Protein Stability in the Different Functional Forms of the SARS-CoV-2 Spike Trimers : Balancing Stability and Adaptability in BA.1, BA.2 and BA.2.75 Variants

This study compares the stability and adaptability of BA.1, BA.2, and BA.2.75 SARS-CoV-2 spike trimers using simulations and mutational analysis, finding BA.2.75 to be the most stable.

Probing Conformational Landscapes and Mechanisms of Allosteric Communication in the Functional States of the ABL Kinase Domain Using Multiscale Simulations and Network-Based Mutational Profiling of Allosteric Residue Potentials

This study uses multiscale simulations and network-based mutational profiling to analyze conformational dynamics and allosteric communication in the ABL kinase domain, identifying key regulatory hotspots.

Atomistic Simulations and Network-Based Energetic Profiling of Binding and Allostery in the SARS-CoV-2 Spike Omicron BA.1, BA.1.1, BA.2 and BA.3 Subvariant Complexes with the Host Receptor: Revealing Hidden Functional Roles of the Binding Hotspots in Mediating Epistatic Effects and Long-Range Communication with Allosteric Pockets

This study uses atomistic simulations and network analysis to quantify binding energy hotspots and epistatic effects in Omicron subvariant RBD-ACE2 complexes.

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

This study integrates conformational dynamics and perturbation-based network modeling to analyze mutational escape mechanisms in SARS-CoV-2 spike variants bound to antibodies.

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

This study uses atomistic simulations and perturbation-based network modeling to analyze mutational profiles of Hsp90 binding and allostery in complexes with cochaperones and client proteins, revealing conserved allosteric switches that regulate client integration.

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

This paper uses computational methods to analyze ALPL mutations in Hypophosphatasia, finding that severe mutations significantly affect allosteric communications and protein stability.

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

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

This study analyzes how nanobodies interact with SARS-CoV-2 spike protein and how mutations like E484A affect their binding, revealing mechanisms of mutational escape and resilience.

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

This study analyzes the conformational dynamics and mutational sensitivity of the SARS-CoV-2 D614G spike mutant using simulations and network analysis, finding increased conformational adaptability and allosteric regulation.

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

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

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

This study analyzes the functional effects of the D614G mutation in SARS-CoV-2 spike proteins using computational methods, revealing its role in enhancing infectivity through stability changes in residue interaction networks.

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

This study identifies structurally adaptable allosteric hotspots in the SARS-CoV-2 spike protein that are targeted by mutations and antibodies, showing their role in modulating binding affinity and stability.

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

This study uses computational methods to analyze how the D614G mutation in SARS-CoV-2 spike protein affects stability and allosteric communication, showing it enhances infectivity through structural changes.

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

This study uses coevolutionary analysis and network modeling to show antibodies modulate allosteric interactions and signaling in SARS-CoV-2 spike proteins, revealing mechanisms for therapeutic targeting.