Vladimir M. Yarov-Yarovoy

The paper investigates how hERG blockers like nifekalant can increase K+ channel current through an agonism-while-blocking mechanism, potentially explaining their safety profile.

This study investigates the effects of ML218 and Z944 on Cav1.4 channels, finding they inhibit Cav1.4 with lower IC50 values than Cav1.2 and highlight the role of methionine residues in ML218's mechanism.

This study uses AlphaFold2 to model multiple conformations of voltage-gated sodium channels and their interactions with protein partners, revealing structural diversity and conformational changes.

This study shows 14-3-3 promotes CaV1.2 sarcolemmal expression and nucleates its super-clustering in response to isoproterenol in cardiomyocytes.

The paper develops RosettaVS, an AI-accelerated virtual screening platform that identifies drug candidates with high binding affinity across two targets, achieving a 14% and 44% hit rate in under seven days.

This study evaluates two ligand docking methods for ion channel complexes, finding they can sample near-native poses but struggle to consistently identify them as top-scoring models.

The paper uses two Kv2 inhibitors to distinguish Kv2/KvS heteromer conductances from Kv2-only channels in neurons.

The paper develops structural models of beta-1 and beta-2 adrenergic receptors with beta-blockers using RosettaLigand and MD simulations, identifying structural features and stability but not clearly distinguishing stereospecific drug preferences.

The paper identifies a single amino acid residue that determines reciprocal specificity between two mosquito odorant receptors for oviposition attractants.

The paper shows H3K4me1 recruits DNA repair proteins to reduce mutations in functionally constrained regions of plant genomes.

The paper presents a framework for ensuring reproducibility in bio-macromolecular modeling through automated benchmarks and a test server, demonstrating its utility for Rosetta and other tools.

This paper develops a multiscale computational model to predict cardiotoxicity from drug chemistry to cardiac rhythm, validated using clinical data and showing high predictive accuracy for arrhythmia vulnerability.

The paper shows that Alpha-Actinin-1 enhances CaV1.2 channel activity by localizing it to specific sites and increasing its open probability.