4 papers
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…
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…
SiamNAS: Siamese Surrogate Model for Dominance Relation Prediction in Multi-objective Neural Architecture Search
Yuyang Zhou, Ferrante Neri, Yew-Soon Ong +1
Modern neural architecture search (NAS) is inherently multi-objective, balancing trade-offs such as accuracy, parameter count, and computational cost. This complexity makes NAS com…
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…