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.
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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
[Description truncada. Veja o README completo no GitHub.]
