Does this skill support 3D molecular modeling?

Yes, it includes patterns for generating 3D coordinates using ETKDG and optimizing molecular geometry with force fields like UFF and MMFF94.

How does RDKit help with molecular similarity?

The skill guides Claude in generating various fingerprints (Morgan, MACCS, etc.) and calculating similarity metrics like Tanimoto or Dice for molecular comparison.

Can I use this for batch processing large molecular datasets?

Absolutely. It provides implementation strategies for using SDMolSuppliers and multithreaded processing for handling large SDF and SMILES files efficiently.

What is the primary purpose of the RDKit skill for Claude?

The RDKit skill provides domain-specific patterns and guidance to help Claude perform cheminformatics tasks like molecular parsing, property calculation, and substructure searching.

RDKit Cheminformatics Toolkit

Name: RDKit Cheminformatics Toolkit
Author: K-Dense-AI

byK-Dense-AI

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3,719

Data Science & ML

Facilitates advanced molecular analysis and cheminformatics workflows including property calculation, substructure searching, and 3D coordinate generation.

About

The RDKit skill provides Claude with specialized patterns and domain-specific guidance for executing complex cheminformatics tasks. It enables the precise manipulation of molecular structures through SMILES/SDF parsing, automated sanitization, and the calculation of critical descriptors like LogP and TPSA. Whether performing high-throughput virtual screening, implementing chemical reactions via SMARTS, or generating optimized 3D conformers for drug discovery, this skill ensures Claude applies the most efficient algorithms and best practices for computational chemistry and molecular modeling.

Key Features

Advanced substructure searching using SMARTS patterns
3,719 GitHub stars
Chemical property and descriptor calculation including Lipinski's Rule of Five
Molecular I/O support for SMILES, SDF, MOL, and InChI formats
Molecular fingerprinting and similarity analysis for library clustering
2D/3D coordinate generation and force field geometry optimization

Use Cases

Visualizing and sanitizing large-scale chemical libraries for research
Developing drug discovery pipelines and automated lead optimization scripts
Generating molecular descriptors for machine learning and QSAR modeling

About

Key Features

Advanced substructure searching using SMARTS patterns
3,719 GitHub stars
Chemical property and descriptor calculation including Lipinski's Rule of Five
Molecular I/O support for SMILES, SDF, MOL, and InChI formats
Molecular fingerprinting and similarity analysis for library clustering
2D/3D coordinate generation and force field geometry optimization

Use Cases

Visualizing and sanitizing large-scale chemical libraries for research
Developing drug discovery pipelines and automated lead optimization scripts
Generating molecular descriptors for machine learning and QSAR modeling