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.]