Dmytro S. Radchenko

The paper identifies TAAR1 agonists with antipsychotic-like effects through computational screening and experimental validation, showing improved potency and reduced side effects in a schizophrenia model.

This study uses library docking to identify subtype-selective CB2 receptor ligands, finding improved hit rates and affinities with larger libraries and structure-based optimization.

The paper introduces CombiDOCK and MINT-Dock to efficiently screen large molecule libraries for ligand discovery, achieving high hit rates and computational efficiency.

Shape-based fragment merging (FrankenROCS) with Thompson sampling over 22 billion molecules found neutral SARS-CoV-2 macrodomain inhibitors; analogs reached single-digit micromolar IC50, backed by 137 crystal structures.

This paper tests the impact of library size and testing scale on virtual screening by comparing results from 1.7 billion vs. 99 million molecule libraries against AmpC β-lactamase, finding improved hit rates and potency with larger libraries.

AdaptiveFlow enables large-scale virtual screening of 69 billion molecules to discover validated FSP1 inhibitors, improving efficiency and scalability in drug discovery.