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diffdock-molecular-docking
Diffusion-based molecular docking to predict 3D ligand–protein binding poses (blind docking) with confidence scoring; use when you need pose prediction for drug discovery or virtual screening.
scientific-skills/Evidence Insight/diffdock-molecular-docking/SKILL.md
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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# DiffDock Molecular Docking
## When to Use
- **Blind docking** when you have a protein structure (PDB) and a ligand (SMILES) but no known binding site.
- **Pose prediction** to generate multiple plausible 3D binding conformations and rank them.
- **Virtual screening support** to quickly evaluate candidate ligands by predicted binding poses and confidence.
- **Drug discovery workflows** where you need automated docking outputs (SDF poses + scores) for downstream analysis.
- **Batch/advanced docking** when running many ligand–protein pairs or using alternative inputs (e.g., sequence-based workflows; see `references/workflows_examples.md`).
## Key Features
- **Diffusion generative sampling** to produce diverse ligand binding poses.