DiffDock Molecular Docking
Predict how small molecules bind to proteins using AI-powered molecular docking.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/diffdock-nim-nvidia/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
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 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 $NGC_API_KEY. Supported local Docker
startup uses NGC_API_KEY (or NVIDIA_API_KEY via the preflight) for
registry login, entitlement checks, and first-run model downloads; pass it
into the container with -e NGC_API_KEY. 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, NVIDIA_API_KEY fallback,
LOCAL_NIM_CACHE, NVIDIA_VISIBLE_DEVICES=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:
until curl -sf http://localhost:8000/v1/health/ready; do sleep 5; done
Prepare Inputs
Protein receptor must be ATOM records only. Strip headers, water, and HETATM.
from pathlib import Path
raw_pdb = Path("protein.pdb").read_text()
protein = "\n".join(line for line in raw_pdb.splitlines() if line.startswith("ATOM"))
if not protein:
raise ValueError("protein.pdb has no ATOM records")
Ligand options:
- SMILES:
ligand = "CC(=O)OC1=CC=CC=C1C(=O)O";ligand_file_type = "txt". - SDF:
ligand = Path("ligand.sdf").read_text();ligand_file_type = "sdf". - MOL2:
ligand_file_type = "mol2".
Do not use "smiles" as ligand_file_type; SMILES is "txt".
Request Pattern
import os
import requests
HOSTED = True
url = (
"https://health.api.nvidia.com/v1/biology/mit/diffdock"
if HOSTED else "http://localhost:8000/molecular-docking/diffdock/generate"
)
headers = {"Content-Type": "application/json"}
if HOSTED:
headers["Authorization"] = f"Bearer {os.getenv('NGC_API_KEY')}"
payload = {
"protein": protein,
"ligand": ligand,
"ligand_file_type": ligand_file_type,
"num_poses": 10,
"time_divisions": 20,
"steps": 18,
"save_trajectory": False,
}
response = requests.post(url, headers=headers, json=payload, timeout=300)
response.raise_for_status()
result = response.json()
Save And Report Output
ligand_positions and position_confidence are parallel ranked lists.
position_confidence[0] is the rank-1 pose confidence.
Save the ranked pose SDFs using the snippet in
references/examples.md under Save Ranked Poses.
View pose SDF files with the receptor in PyMOL, ChimeraX, or UCSF Chimera. For
pose sanity checks and confidence caveats, read references/validation.md.
Limits And Troubleshooting
- Max
num_poses: 100. Maxtime_divisions: 20. Maxsteps: 18. - Single GPU; local minimum is about 24 GB VRAM.
422: invalidligand_file_type, invalid SMILES/SDF, or no ATOM records.- Empty poses: validate receptor ATOM records and ligand parseability.
- Local URL 404 usually means the wrong hosted path or an accidental
/v1/.
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