DiffDock Molecular Docking

About

DiffDock is a state-of-the-art computational biology tool designed to predict the 3D orientation (binding pose) of small molecule ligands within protein targets. By leveraging diffusion models, it provides high-accuracy structural predictions that are essential for virtual screening, lead optimization, and chemical biology research. While it focuses on structural configuration and prediction confidence rather than direct binding affinity, it integrates seamlessly into drug discovery pipelines by supporting batch processing, protein sequences via ESMFold, and compatibility with downstream scoring functions like GNINA.

Key Features

• Support for protein PDB files or raw amino acid sequences via ESMFold
• Flexible ligand input handling including SMILES, SDF, and MOL2
• 1 GitHub stars
• High-accuracy 3D binding pose prediction using diffusion models
• Batch processing for large-scale virtual screening campaigns
• Reliability assessment through automated confidence scoring

Use Cases

• Virtual screening of large compound libraries against specific receptors
• Structure-based drug discovery and lead compound optimization
• Identifying potential binding sites for novel protein targets