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About diffdock
diffdock
Predicts protein-small-molecule binding poses
diffdock is an agent skill for predicting protein and small-molecule binding poses with DiffDock and DiffDock-L. You can start from a PDB structure or a protein sequence, and a ligand given as SMILES, SDF or MOL2. The model generates candidate ligand poses and ranks them by model confidence. The skill is clear that confidence is neither a measured probability of correctness nor a binding affinity. It covers a single protein-ligand pair, batch docking, and runs against separate receptor conformations. It advises treating a library-wide sort by confidence as pose triage, not as hit identification. The skill targets DiffDock v1.1.3. Its source and the current main branch's inference script were checked on 30 September 2026. Bundled helpers were tested on tiny synthetic inputs, but pretrained docking, ESMFold, CUDA, Docker, GNINA and hosted demo runs were not executed in that review. The skill labels the commands that need those components as source-verified recipes rather than demonstrated end-to-end runs. It also includes steps for setting up the upstream environment. It is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/diffdock