Guangfeng Zhou

An atom-level graph neural network that denoises corrupted structures generates small-molecule and protein-ligand conformational ensembles, and its active-site pre-organization metric enriched for more active designed retroaldolases.

This paper introduces EMERALD-ID, a method for identifying small molecules in cryo-EM data, achieving 43% exact identification and 66% close identification of common ligands.

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.