5 papers
BindCLIP: A Unified Contrastive-Generative Representation Learning Framework for Virtual Screening
Anjie Qiao, Zhen Wang, Yaliang Li +2
Virtual screening aims to efficiently identify active ligands from massive chemical libraries for a given target pocket. Recent CLIP-style models such as DrugCLIP enable scalable v…
A Novel Framework for Multi-Modal Protein Representation Learning
Runjie Zheng, Zhen Wang, Anjie Qiao +3
Accurate protein function prediction requires integrating heterogeneous intrinsic signals (e.g., sequence and structure) with noisy extrinsic contexts (e.g., protein-protein intera…
Composable Score-based Graph Diffusion Model for Multi-Conditional Molecular Generation
Anjie Qiao, Zhen Wang, Chuan Chen +2
Controllable molecular graph generation is essential for material and drug discovery, where generated molecules must satisfy diverse property constraints. While recent advances in…
A 3D pocket-aware and evolutionary conserved interaction guided diffusion model for molecular optimization
Anjie Qiao, Hao Zhang, Qianmu Yuan +7
Generating molecules that bind to specific protein targets via diffusion models has shown good promise for structure-based drug design and molecule optimization. Especially, the di…
A 3D pocket-aware and affinity-guided diffusion model for lead optimization
Anjie Qiao, Junjie Xie, Weifeng Huang +7
Molecular optimization, aimed at improving binding affinity or other molecular properties, is a crucial task in drug discovery that often relies on the expertise of medicinal chemi…