1 code implementation • 20 May 2024 • Eric Alcaide, Zhifeng Gao, Guolin Ke, Yaqi Li, Linfeng Zhang, Hang Zheng, Gengmo Zhou
In recent years, machine learning (ML) methods have emerged as promising alternatives for molecular docking, offering the potential for high accuracy without incurring prohibitive computational costs.
no code implementations • 14 Feb 2023 • Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke
However, to our surprise, we design a simple and cheap algorithm (parameter-free) based on the traditional methods and find it is comparable to or even outperforms deep learning based MCG methods in the widely used GEOM-QM9 and GEOM-Drugs benchmarks.
no code implementations • 18 Sep 2022 • Yang Zhang, Gengmo Zhou, Zhewei Wei, Hongteng Xu
The prediction of protein-ligand binding affinity is of great significance for discovering lead compounds in drug research.
1 code implementation • ChemRxiv 2022 • Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke
Uni-Mol is composed of two models with the same SE(3)-equivariant transformer architecture: a molecular pretraining model trained by 209M molecular conformations; a pocket pretraining model trained by 3M candidate protein pocket data.
Ranked #1 on Molecular Property Prediction on MUV