SkillAgentSearch skills...

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.

Install / Use

npx skills add NVIDIA/skills --skill bionemo-diffdock-nim

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

87/100

Category

Operations

Supported Platforms

Universal

Our assessment of diffdock-nim

diffdock-nim scores 87/100 on our quality scale, 452nd of 751 Operations skills we index.

Its SKILL.md is 4.2 KB long, split into 7 sections with 3 code examples: a solid amount of guidance for an agent.

With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
16/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 16 days ago, so diffdock-nim is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

diffdock-nim compared with similar skills

All 4 of these similar skills score higher than diffdock-nim; compare them before choosing.

SkillScoreStarsUpdatedFormat
diffdock-nim (this skill)by NVIDIA873.4k16d agoSKILL.md
Agent-Reachby Panniantong10095.3k2d agoCLAUDE.md
headroomby headroomlabs-ai10074.9ktodayCLAUDE.md
Scraplingby D4Vinci10086.6k1d agoMCP Server
crawl4aiby unclecode10085.1k5d agoMCP Server

Frequently asked questions

How do I install diffdock-nim?
Run npx skills add NVIDIA/skills --skill diffdock-nim. The install tabs above show the steps for each supported agent.
Which AI agents does diffdock-nim work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is diffdock-nim safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is diffdock-nim still maintained?
The repository was last updated 16 days ago, so diffdock-nim is actively maintained.

name: diffdock-nim description: > 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. license: Apache-2.0 AND CC-BY-4.0 compatibility: "requests>=2.28" allowed-tools: Bash, Read, Write, AskUserQuestion

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. Max time_divisions: 20. Max steps: 18.
  • Single GPU; local minimum is about 24 GB VRAM.
  • 422: invalid ligand_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/.

Related Skills

View on GitHub
GitHub Stars3.4k
CategoryOperations
Updated16d ago
Forks412

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions