Is cloud storage supported?

Yes, Datamol integrates with fsspec to allow reading and writing molecular files directly from S3, Google Cloud Storage, or HTTP endpoints.

Datamol is a Python library that provides a simplified, Pythonic interface for RDKit, making molecular data manipulation easier and more efficient.

Can I process large datasets with this skill?

Absolutely. Datamol includes built-in parallelization and batch processing functions designed for handling thousands of molecules efficiently.

Does Datamol work with standard RDKit objects?

Yes, Datamol returns native rdkit.Chem.Mol objects, ensuring full compatibility with the existing RDKit ecosystem.

Does it support 3D structure generation?

Yes, it includes advanced modules for 3D conformer generation, energy minimization, and solvent-accessible surface area (SASA) calculations.

Datamol Cheminformatics

Name: Datamol Cheminformatics
Author: Zehong-Wang

byZehong-Wang

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Data Science & ML

Simplifies molecular cheminformatics workflows with a Pythonic wrapper for RDKit, featuring structure standardization, descriptor calculation, and 3D conformer generation.

Datamol is an essential skill for researchers and developers working in drug discovery and molecular science, providing a high-level, efficient interface for the RDKit library. It streamlines complex chemical data tasks such as SMILES parsing, molecular standardization, and fingerprint generation while maintaining full compatibility with native RDKit objects. By offering sensible defaults, built-in parallelization, and support for cloud-based file systems, Datamol enables Claude to assist in building robust scientific pipelines, performing scaffold analysis, and visualizing chemical structures with minimal boilerplate code.

Key Features

01Automated structure standardization and sanitization workflows

02Molecular format conversion for SMILES, SELFIES, and InChI

03Advanced scaffold analysis and Murcko decomposition for library design

04High-performance batch computation of molecular descriptors and fingerprints

053D conformer generation with RMSD-based clustering and energy minimization

060 GitHub stars

Use Cases

01Generating 3D molecular conformations for docking and energy calculations

02Standardizing and cleaning large molecular datasets for machine learning models

03Performing structural diversity selection and clustering for compound library design

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zehong-wang/kosmos datamol

For use in Claude.ai and ChatGPT

Download Skill