7 papers
VecMol: Vector-Field Representations for 3D Molecule Generation
Yuchen Hua, Xingang Peng, Jianzhu Ma +1
Generative modeling of three-dimensional (3D) molecules is a fundamental yet challenging problem in drug discovery and materials science. Existing approaches typically represent mo…
Peptide2Mol: A Diffusion Model for Generating Small Molecules as Peptide Mimics for Targeted Protein Binding
Xinheng He, Yijia Zhang, Haowei Lin +4
Structure-based drug design has seen significant advancements with the integration of artificial intelligence (AI), particularly in the generation of hit and lead compounds. Howeve…
Assay2Mol: large language model-based drug design using BioAssay context
Yifan Deng, Spencer S. Ericksen, Anthony Gitter
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…
Geometric Representation Condition Improves Equivariant Molecule Generation
Zian Li, Cai Zhou, Xiyuan Wang +2
Recent advances in molecular generative models have demonstrated great promise for accelerating scientific discovery, particularly in drug design. However, these models often strug…
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
Xingang Peng, Shitong Luo, Jiaqi Guan +3
Deep generative models have achieved tremendous success in designing novel drug molecules in recent years. A new thread of works have shown the great potential in advancing the spe…
Group Ligands Docking to Protein Pockets
Jiaqi Guan, Jiahan Li, Xiangxin Zhou +5
Molecular docking is a key task in computational biology that has attracted increasing interest from the machine learning community. While existing methods have achieved success, t…