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diffdock

combined

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. Predicts protein-small-molecule binding poses with DiffDock and DiffDock-L from PDB or sequence plus SMILES/SDF/MOL2. Covers batch docking, pose triage, confidence interpretation, and validation. Use for molecular docking and virtual-screening pose generation, not binding-affinity prediction.

When to use

• "Dock this ligand to a protein" or "predict binding pose"
• "Run molecular docking" or "perform protein-ligand docking"
• "Virtual screening" or "screen compound library"
• "Where does this molecule bind?" or "predict binding site"
• Structure-based drug design or lead optimization tasks
• Tasks involving PDB files + SMILES strings or ligand structures
• Batch docking of multiple protein-ligand pairs

When not to use

• affinity prediction
• binding affinity assessment
• ΔG calculation
• Kd calculation

Skill page

Conflict

The K-Dense copy is a rigorous, source-verified procedure that pins the v1.1.3 release, corrects the CLI flag to --ligand_description, and details input preparation and output file naming. The FreedomIntelligence copy is a broader workflow guide that includes a results analysis script (analyze_results.py) and a pre-computed ESM embedding workflow for large-scale screening, which are absent from the K-Dense copy. The FreedomIntelligence copy also uses the incorrect --ligand flag and lacks the specific version pinning and input validation constraints found in the K-Dense copy. Combining them provides a complete, accurate, and scalable docking workflow.