数据与复现蛋白结构与设计FreedomIntelligence/OpenClaw-Medical-Skills数据与复现

bio-molecular-descriptors

维护者 FreedomIntelligence · 最近更新 2026年4月1日

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.

OpenClawNanoClaw分析处理复现实验bio-molecular-descriptors🧬 bioinformatics (gptomics bio-* suite)bioinformatics — structural biology & cheminformaticscalculates

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

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

维护者: FreedomIntelligence
许可: MIT
最近更新: 2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

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

原始文档

SKILL.md 摘录

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)