6 papers
BioLM-Score: Language-Prior Conditioned Probabilistic Geometric Potentials for Protein-Ligand Scoring
Zhangfan Yang, Baoyun Chen, Dong Xu +4
Protein-ligand scoring is a central component of structure-based drug design, underpinning molecular docking, virtual screening, and pose optimization. Conventional physics-based e…
From Tokens to Blocks: A Block-Diffusion Perspective on Molecular Generation
Qianwei Yang, Dong Xu, Zhangfan Yang +4
Drug discovery can be viewed as a combinatorial search over an immense chemical space, motivating the development of deep generative models for de novo molecular design. Among thes…
Toward Closed-loop Molecular Discovery via Language Model, Property Alignment and Strategic Search
Junkai Ji, Zhangfan Yang, Dong Xu +4
Drug discovery is a time-consuming and expensive process, with traditional high-throughput and docking-based virtual screening hampered by low success rates and limited scalability…
IBEX: Information-Bottleneck-EXplored Coarse-to-Fine Molecular Generation under Limited Data
Dong Xu, Zhangfan Yang, Jenna Xinyi Yao +3
Three-dimensional generative models increasingly drive structure-based drug discovery, yet it remains constrained by the scarce publicly available protein-ligand complexes. Under s…
MODA: A Unified 3D Diffusion Framework for Multi-Task Target-Aware Molecular Generation
Dong Xu, Zhangfan Yang, Sisi Yuan +3
Three-dimensional molecular generators based on diffusion models can now reach near-crystallographic accuracy, yet they remain fragmented across tasks. SMILES-only inputs, two-stag…
Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screening
Zhangfan Yang, Junkai Ji, Shan He +5
Molecular docking is a crucial step in drug development, which enables the virtual screening of compound libraries to identify potential ligands that target proteins of interest. H…