Lingang Laboratory
A Shanghai life-science laboratory tackling biomedicine and brain disease through AI-driven molecular design and single-cell biology.
Models (5)
AuroBind
Shanghai Jiao Tong University / Lingang Laboratory / Sun Yat-sen University / Fudan University / Shanghai AI Laboratory / Shanghai Institute of Materia Medica / MIT / Ningxia Medical University
Released August 4, 2025
Structure-based virtual screening model that jointly predicts protein-ligand complex structures and binding fitness from sequence and SMILES.
MolPIF
Lingang Laboratory / Shanghai Institute of Materia Medica / ShanghaiTech University / Fudan University / Shanghai Jiao Tong University
Released July 18, 2025
Structure-based drug design model that generates 3D ligands inside a protein pocket by interpolating distribution parameters instead of samples.
BrainBeacon
Lingang Laboratory / Shanghai Academy of Artificial Intelligence for Science / Shanghai Institute of Biochemistry and Cell Biology / Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences / Institute of Neuroscience, Chinese Academy of Sciences / Shanghai Jiao Tong University / University of Chinese Academy of Sciences / University of Tokyo
Released July 10, 2025
Cross-species brain spatial transcriptomics foundation model pretrained on 133M cells from human, macaque, marmoset, and mouse whole brains.
PBCNet2.0
Shanghai Institute of Materia Medica / ShanghaiTech University / Lingang Laboratory / University of Chinese Academy of Sciences / Tongji University / University of Science and Technology of China / Nanjing University of Chinese Medicine / Zunyi Medical University / Guizhou Medical University
Released June 4, 2025
Relative protein-ligand binding affinity prediction from docked complexes, matching Schrodinger FEP+ ranking accuracy zero-shot on the FEP benchmark.
PhysDock
ShanghaiTech University / Lingang Laboratory / Australian National University / Cellverse
Released May 2, 2025
Physics-guided all-atom diffusion model for protein-ligand complex prediction, reaching 95.3% success on PoseBusters redocking with a known pocket.