V. Yarov-Yarovoy

This study uses computational modeling to investigate how protoxin-2 binds to different states of the hNaV1.7 channel, identifying key residues and lipid interactions that contribute to its selectivity.

The paper identifies molecular interactions between μ-conotoxin KIIIA and hNaV1.7 using computational modeling, experimental validation, and structural analysis.

The paper measures how RTX binding to TRPV1 subunits affects channel opening, finding each subunit contributes equally to activation energy.

The paper designs potent and selective peptide inhibitors of human NaV1.7 channels using Rosetta, with two peptides showing sub-nanomolar IC50 and high selectivity over other sodium channels.

The paper applies RosettaDock to model peptide toxin - ion channel interactions, showing it can sample near-native structures for 10 tested complexes.

This study uses Rosetta to model structural changes in hERG channels caused by mutations and drug interactions, revealing conformational shifts and binding mechanisms.

This study identifies an unconventional voltage-sensing mechanism in TRPV1 channels where outer pore acidic residues, not the S4 segment, mediate voltage sensitivity and activation.

This paper develops a computational framework to distinguish safe and unsafe hERG blockers by modeling atomic interactions and simulating drug-channel dynamics.

This study investigates the molecular interactions of antiarrhythmic and local anesthetic drugs with hNav1.5 using structural modeling and simulations, revealing key binding sites and pathways.