DiffDock: Molecular Docking with Diffusion Models

--- name: diffdock description: "Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction." --- # DiffDock: Molecular Docking with Diffusion Models ## Overview DiffDock is a diffusion-based deep learning tool for molecular docking that predicts 3D binding poses of small molecule ligands to protein targets. It represents the state-of-the-art in computational docking, crucial for structure-based drug discovery and chemical biology. **Core Capabilities:** - Predict ligand binding poses with high accuracy using deep learning - Support protein structures (PDB files) or sequences (via ESMFold) - Process single complexes or batch virtual screening campaigns - Generate confidence scores to assess prediction reliability - Handle diverse ligand inputs (SMILES, SDF, MOL2) **Key Distinction:** DiffDock predicts **binding poses** (3D structure) and **confidence** (