Data & ReproProtein Structure & DesignFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction
BI

bio-molecular-descriptors

Maintainer FreedomIntelligence · Last updated April 1, 2026

Calculates molecular descriptors and fingerprints using RDKit. Computes Morgan fingerprints (ECFP), MACCS keys, Lipinski properties, QED drug-likeness, TPSA, and 3D conformer descriptors. Use when featurizing molecules for machine learning or filtering by drug-likeness criteria.

OpenClawNanoClawAnalysisReproductionbio-molecular-descriptors🧬 bioinformatics (gptomics bio-* suite)bioinformatics — structural biology & cheminformaticscalculates

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-molecular-descriptors

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • Python: AllChem.GetMorganFingerprintAsBitVect(), Descriptors.MolWt(), QED.qed() (RDKit).
  • Calculate molecular fingerprints for my compound library" → Compute structural fingerprints (Morgan/ECFP, MACCS keys) and physicochemical descriptors (Lipinski, QED, TPSA) for molecules, producing feature vectors for similarity analysis or ML models. Python: AllChem.GetMorganFingerprintAsBitVect(), Descriptors.MolWt(), QED.qed() (RDKit).
  • Calculate fingerprints and physicochemical properties for molecules.
  • ecfp4 = AllChem.GetMorganFingerprintAsBitVect(mol, radius=2, nBits=2048) ecfp6 = AllChem.GetMorganFingerprintAsBitVect(mol, radius=3, nBits=2048).

Source Doc

Excerpt From SKILL.md

Morgan Fingerprints (ECFP)

Goal: Generate circular fingerprints that encode local chemical environments for similarity searching and ML models.

Approach: Use GetMorganFingerprintAsBitVect with a chosen radius (2 for ECFP4, 3 for ECFP6) and bit length, optionally including chirality information.

from rdkit import Chem
from rdkit.Chem import AllChem

mol = Chem.MolFromSmiles('CCO')

## With stereochemistry information

ecfp4_chiral = AllChem.GetMorganFingerprintAsBitVect(
    mol, radius=2, nBits=2048, useChirality=True
)

## As count vector (for some ML methods)

ecfp4_counts = AllChem.GetMorganFingerprint(mol, radius=2)

Use cases

  • Use when featurizing molecules for machine learning or filtering by drug-likeness criteria.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • molecular-io - Load molecules for descriptor calculation
  • similarity-searching - Use fingerprints for similarity
  • admet-prediction - Predict ADMET from descriptors
  • machine-learning/biomarker-discovery - ML on molecular features

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