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datamol

Parse, standardize, and compute molecular descriptors with Python and RDKit.

13|3|Updated Jun 10, 2026
Search Tags:#RDKit#datamol#molecule processing#molecular cheminformatics#descriptor computation
One-click install
npx skills add https://github.com/tassiovale/claude-code-kit --skill datamol-tassiovale
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datamol
Source: https://github.com/tassiovale/claude-code-kit/tree/main/skills/datamol
Command: npx skills add https://github.com/tassiovale/claude-code-kit --skill datamol-tassiovale

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rdkit, datamol, fsspec, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies complex molecular cheminformatics tasks using Python and RDKit, allowing users to parse, standardize, compute descriptors, and perform various analyses with ease.

Core Features & Use Cases

  • Molecular Processing: Efficiently parse, standardize, and manipulate molecular structures in SMILES, InChI, and SELFIES formats.
  • Descriptor Calculation: Compute a comprehensive set of molecular descriptors, including molecular weight, logP, TPSA, and more.
  • Fragmentation and Scaffold Analysis: Fragment molecules into substructures and analyze scaffold diversity for drug design and SAR studies.
  • 3D Conformer Generation: Generate and analyze 3D conformers for molecular visualization and analysis.
  • Reaction Application: Apply chemical reactions using SMARTS patterns to transform molecules and explore retrosynthesis.
  • Visualization: Generate visual representations of molecules and conformers for easy interpretation.
  • Use Case: A researcher can use this Skill to process a large set of compounds, compute their descriptors, cluster them based on similarity, and generate 3D conformers for analysis.

Quick Start

Use the datamol skill to standardize and compute descriptors for all molecules in the 'molecules.sdf' file.

Frequently Asked Questions about datamol

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I standardize molecules in SMILES or InChI formats using RDKit?▼

Molecular standardization in SMILES, InChI, and SELFIES formats is handled by parsing and manipulating molecular structures through RDKit. This Skill simplifies the standardization process, allowing you to efficiently process large sets of compounds.

Can I compute molecular descriptors like logP and TPSA in Python?▼

Yes, you can compute a comprehensive set of molecular descriptors, including molecular weight, logP, and TPSA, directly in Python. The Skill uses RDKit and datamol to calculate these properties for compound analysis.

Do I need RDKit installed to generate 3D conformers and perform scaffold analysis?▼

Yes, RDKit and Python 3.8+ are required for molecule processing, 3D conformer generation, and scaffold analysis. Optional fsspec is needed if you require cloud I/O capabilities.

What's the best way to fragment molecules into substructures for drug design?▼

Fragmenting molecules into substructures for drug design and SAR studies is best achieved through scaffold analysis. This Skill provides tools to fragment molecules and analyze scaffold diversity efficiently.

How do I apply chemical reactions using SMARTS patterns to transform molecules?▼

Applying chemical reactions using SMARTS patterns allows you to transform molecules and explore retrosynthesis. This Skill enables reaction application directly within your Python cheminformatics workflow.

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