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Predict biomolecular structures with Boltz2 v1.0.0

Use this resource to predict biomolecular complex structures and estimate their binding affinity with Boltz2

New

  • 529 downloads
  • 231 likes
  • 117 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install biomolecular-structure-prediction-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 the mode (hosted NVIDIA API or local Docker), builds the request from your sequences and ligands, then saves the result in mmCIF with confidence scores. It also checks ligand chemistry.

Mostly picked by

Updated November 2, 2026

Card for the “Predict biomolecular structures with Boltz2” skill

Details

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

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What you get

  • SKILL.md : procedure and output rules
  • references/parameters.md : prediction and affinity settings
  • references/validation.md : mmCIF, confidence and chemistry checks

Good fit for

  • You want to model a protein with a small ligand
  • You want an affinity score to rank candidates

Not for

    Tags

    • boltz2
    • proteins
    • affinity
    • structure
    • biology

    About

    You say

    “Predict the structure of this protein in complex with this SMILES ligand, and give the affinity.”

    Card for the “Predict biomolecular structures with Boltz2” 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 biomolecular complex structures and estimate their binding affinity with Boltz2
    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.json6.7 KB
    • evals/trigger_evals.json2.3 KB
    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/api.md5.8 KB
    • references/examples.md2.1 KB
    • references/parameters.md1.7 KB
    • references/science.md1.7 KB
    • references/validation.md1.3 KB
    • skill-card.md4.2 KB
    • SKILL.md5.5 KB
    • skill.oms.sig6.3 KB

    Origin and licence

    Listed unmodified

    Author
    nvidia
    Source
    github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/bionemo-boltz2-nim
    Licence
    CC-BY-4.0

    Notice

    « boltz2-nim » (nvidia, CC-BY-4.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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