G. Verkhivker

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.

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.

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

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.

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.

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.

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

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

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.

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

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.

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.

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.

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.

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.

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.