3 papers
q-bio.QM2026
Empowering Chemical Structures with Biological Insights for Scalable Phenotypic Virtual Screening
Xiaoqing Lian, Pengsen Ma, Tengfeng Ma +9
Motivation: The scalable identification of bioactive compounds is essential for contemporary drug discovery. This process faces a key trade-off: structural screening offers scalabi…
cs.CL2025
Enhancing Molecular Property Prediction with Knowledge from Large Language Models
Peng Zhou, Lai Hou Tim, Zhixiang Cheng +4
Predicting molecular properties is a critical component of drug discovery. Recent advances in deep learning, particularly Graph Neural Networks (GNNs), have enabled end-to-end lear…
physics.chem-ph2025
EDBench: Large-Scale Electron Density Data for Molecular Modeling
Hongxin Xiang, Ke Li, Mingquan Liu +7
Existing molecular machine learning force fields (MLFFs) generally focus on the learning of atoms, molecules, and simple quantum chemical properties (such as energy and force), but…