DiffDock and DiffDock-PP

About DiffDock

gcorso/DiffDock

Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Leverages equivariant diffusion models to jointly predict ligand position, orientation, and conformational changes in 3D space, with built-in confidence scoring for pose quality assessment. Supports flexible input formats including PDB files, protein sequences (auto-folded with ESMFold), SMILES strings, and batch processing via CSV, running efficiently on GPU or CPU. DiffDock-L, the latest version, significantly improves generalization and performance; the framework integrates with standard cheminformatics tools (RDKit) and provides deployment options including Hugging Face Spaces, local UI, and Docker containers.

About DiffDock-PP

ketatam/DiffDock-PP

Implementation of DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models in PyTorch (ICLR 2023 - MLDD Workshop)