All Competitors

Blind flexible protein-ligand docking model trained by two-player self-play, predicting bound ligand and pocket poses in 0.32 seconds per complex.

Multi-state protein inverse folding model that designs one sequence for two conformations, improving sequence recovery 12% over ProteinMPNN.

Relative protein-ligand binding affinity prediction from docked complexes, matching Schrodinger FEP+ ranking accuracy zero-shot on the FEP benchmark.

Surrogate machine learning force field reusing a reference model's node features from earlier steps, running molecular dynamics eight times faster.