Agent skill

bio-shape-similarity

Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill shape-similarity --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 13 KB
Bundled scripts: yes
Path: skills/bioskills/shape-similarity/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: RDKit 2024.09+ (Open3DAlign), USRCAT 1.2+, ShaEP 1.7+, ROCS (OpenEye, commercial). Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Shape Similarity Search for compounds with similar 3D shape (and optionally chemical features) to a query molecule. Shape-based screening complements 2D fingerprint search: it can find scaffold-hopped compounds that ECFP4 misses (different scaffolds with similar shape). ROCS (OpenEye) is the industry-standard commercial tool; Open3DAlign (RDKit), USRCAT (Schreyer & Blundell 2012), and ShaEP are open-source alternatives. Modern best practice combines shape with color (chemical-feature similarity) via Tanimoto-Combo: matches share both shape and pharmacophore feature distribution. For 2D fingerprint similarity, see `chemoinformatics/similarity-searching`. For pharmacophore search (discrete feature constraints), see `chemoinformati

What's inside
Steps it walks through
  1. Version Compatibility
  2. Shape Method Taxonomy
  3. Decision Tree by Scenario
  4. Tanimoto-Combo Scoring (ROCS Standard)
  5. USRCAT (Ultra-Fast Shape Recognition + Atom Types)
  6. Open3DAlign (RDKit)
  7. Conformer-Ensemble Shape Searching
  8. ESP Similarity (Electrostatic)
  9. Shape vs ECFP4 Complementarity
  10. Per-Tool Failure Modes
  11. USRCAT -- false positive on small molecules
  12. Open3DAlign -- slow on large library
  13. Shape only -- wrong stereochemistry match
  14. ROCS color -- bioisostere missed
Ships with 2 files
  • examples/shape_search.py
  • usage-guide.md
Commands it runs
shaep --query query.mol2 --target target.mol2 --output match.sdf \
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About this skill
What does the bio-shape-similarity skill do?

Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill shape-similarity --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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