4 papers
Rigidity-Aware Geometric Pretraining for Protein Design and Conformational Ensembles
Zhanghan Ni, Yanjing Li, Zeju Qiu +4
Generative models have recently advanced protein design by learning the statistical regularities of natural structures. However, current approaches face three ke…
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes
Jason Yang, Ariane Mora, Shengchao Liu +4
Enzymes are important proteins that catalyze chemical reactions. In recent years, machine learning methods have emerged to predict enzyme function from sequence; however, there are…
A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics
Shengchao Liu, Weitao Du, Hannan Xu +8
In drug discovery, molecular dynamics (MD) simulation for protein-ligand binding provides a powerful tool for predicting binding affinities, estimating transport properties, and ex…
Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design
Shengchao Liu, Divin Yan, Weitao Du +6
Artificial intelligence models have shown great potential in structure-based drug design, generating ligands with high binding affinities. However, existing models have often overl…