agentsclimarketplace
Sign in

Protein structure prediction

Skill BioTender-max/awesome-bio-agent-skills/skills/openclaw/protein-structure-prediction

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.From the repository description

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill protein-structure-prediction

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

SKILL.md

1.8 KB, 467 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

name: 'protein-structure-prediction' description: 'Predicts 3D protein structures from amino acid sequences using ESMFold or AlphaFold3 (mock).' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Protein Structure Prediction (ESMFold/AF3)

The Protein Structure Prediction Skill provides an interface to state-of-the-art folding models. It takes an amino acid sequence and returns a PDB file or structure metrics (pLDDT).

When to Use This Skill

  • When you have a protein sequence and need its 3D coordinates.
  • To check if a designed sequence folds into a stable structure.
  • To prepare a receptor for docking simulations.

Core Capabilities

  1. Folding: Generates atomic coordinates (PDB format).
  2. Confidence Scoring: Returns pLDDT scores per residue.
  3. Visualization: (Optional) Generates a static view of the structure.

Workflow

  1. Input: Amino acid sequence (FASTA string).
  2. Process: Sends sequence to ESMFold API (or local inference).
  3. Output: Saves .pdb file and returns confidence metrics.

Example Usage

User: "Fold this sequence: MKTIIALSY..."

Agent Action:

python3 Skills/Drug_Discovery/Protein_Structure/esmfold_client.py \
    --sequence "MKTIIALSYIFCLVFDYDY" \
    --output structure.pdb
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 2 files

18.1 KB alongside SKILL.md, 1 of them executable

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.