7 citations · 14 across the 5 of their papers we have counts for
5 papers
Multi-Alignment Contrastive Learning for Enzyme--Reaction Retrieval
Gengmo Zhou, Feng Yu, Wenda Wang +4
Identifying enzymes that catalyze target biochemical reactions is a key step in computational enzyme discovery and biocatalyst design. Recent representation-learning methods formul…
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search
Gengmo Zhou, Zhen Wang, Feng Yu +3
Virtual Screening is an essential technique in the early phases of drug discovery, aimed at identifying promising drug candidates from vast molecular libraries. Recently, ligand-ba…
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction
Eric Alcaide, Zhifeng Gao, Guolin Ke +4
In recent years, machine learning (ML) methods have emerged as promising alternatives for molecular docking, offering the potential for high accuracy without incurring prohibitive…
Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?
Gengmo Zhou, Zhifeng Gao, Zhewei Wei +2
Molecular conformation generation (MCG) is a fundamental and important problem in drug discovery. Many traditional methods have been developed to solve the MCG problem, such as sys…
Predicting Protein-Ligand Binding Affinity via Joint Global-Local Interaction Modeling
Yang Zhang, Gengmo Zhou, Zhewei Wei +1
The prediction of protein-ligand binding affinity is of great significance for discovering lead compounds in drug research. Facing this challenging task, most existing prediction m…