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Molecular docking with DiffDock NIM v1.0.0

Use this resource to predict protein-ligand binding poses with DiffDock NIM

New

  • 474 downloads
  • 124 likes
  • 108 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install diffdock-molecular-docking-nim

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent picks hosted or local mode, prepares the protein and the ligand (SMILES or SDF), then runs blind docking. You get ranked poses with confidence scores, saved with a report.

Mostly picked by

Updated November 2, 2026

Card for the “Molecular docking with DiffDock NIM” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
CC-BY-4.0

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What you get

  • references/api.md: endpoints and schemas
  • references/parameters.md: ligand formats, pose counts and controls
  • references/validation.md: checks on protein, ligand and poses

Good fit for

  • You want to rank candidate ligands against a protein target
  • You test a ligand by blind docking, with no known binding site

Not for

    Tags

    • docking
    • proteins
    • ligand
    • nim

    About

    You say

    “Run blind docking of this SMILES ligand against my PDB protein.”

    Card for the “Molecular docking with DiffDock NIM” skill

    Skill published by nvidia under the CC-BY-4.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to predict protein-ligand binding poses with DiffDock NIM
    3. Review and adjust the result

    Content preview

    Files

    • BENCHMARK.md7 KB
    • config/skillspector-baseline.yml0.9 KB
    • evals/config.yml0.1 KB
    • evals/evals.json6.6 KB
    • evals/files/protein.pdb249.8 KB
    • evals/trigger_evals.json2.2 KB
    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/api.md4.7 KB
    • references/examples.md2.1 KB
    • references/parameters.md1 KB
    • references/science.md2 KB
    • references/validation.md1.8 KB
    • skill-card.md4.4 KB
    • SKILL.md4.3 KB
    • skill.oms.sig6.5 KB

    Origin and licence

    Listed unmodified

    Author
    nvidia
    Source
    github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/bionemo-diffdock-nim
    Licence
    CC-BY-4.0

    Notice

    « diffdock-nim » (nvidia, CC-BY-4.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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