Agent skill · nvidia
diffdock-nim
Run DiffDock molecular docking via NVIDIA NIM to predict small-molecule binding poses against protein targets. Use for DiffDock, molecular docking, ligand docking, blind docking, SMILES or SDF ligands, ranked poses, confidence scores, hosted NVIDIA API, or local Docker deployment.
What it needs
About 2k tokens when loaded.
What this skill does
DiffDock NIM Predict protein-ligand binding poses with blind docking. Use this guide for first-pass hosted/local usage; load supplemental files only when needed: references/api.md: exact hosted/local endpoints, schemas, Docker flags. references/science.md: docking use cases, limits, and handoffs. references/parameters.md: ligand formats, pose counts, diffusion controls. references/validation.md: receptor, ligand, pose, and confidence checks. references/examples.md: compact hosted/local and pose-saving patterns. Choose Mode Ask only when context is unclear: Hosted NVIDIA API or local Docker NIM? Hosted: https://health.api.nvidia.com/v1/biology/mit/diffdock Local: http://localhost:8000/molecular-docking/diffdock/generate The hosted and local paths differ. Local has no /v1/ prefix and uses the /molecular-docking/ route. Hosted requests use Authorization: Bearer $NGCAPIKEY. Supported local Docker startup uses NGCAPIKEY (or NVIDIAAPIKEY via the preflight) for registry login, entitlement checks, and first-run model downloads; pass it into the container with -e NGCAPIKEY. Local inference requests use no auth header after readiness. Warm-cache key-free startup varies by image/version and should not be assumed. Local Docker For the exact local preflight (.env load, NVIDIAAPIKEY fallback, LOCALNIMCACHE, NVIDIAVISIBLEDEVICES=0, --shm-size=2G, both --ulimit flags, docker login, and the docker run for nvcr.io/nim/mit/diffdock:2.2.0), copy the command block in references/api.md under Docker Reference verbatim. Readiness: Prepare Inputs Protein receptor must be ATOM records only. Strip headers, water, and HETATM. Ligand options: SMILES: ligand = "CC(=O)OC1=CC=CC=C1C(=O)O"; ligandfiletype = "txt". SDF: ligand = Path("ligand.sdf").readtext(); ligandfiletype = "sdf". MOL2: ligandfiletype = "mol2". Do not use "smiles" as ligandfiletype; SMILES is "txt". Request Pattern Save And Report Output ligandpositions and positionconfidence are parallel ranked lists. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/bionemo-diffdock-nim