Does Datamol support parallel processing for large datasets?

Yes, Datamol is built with performance in mind and features built-in support for parallelization in descriptor computation, fingerprinting, and file reading.

Can I use Datamol with cloud storage like AWS S3?

Yes, Datamol integrates with fsspec, allowing you to read and write molecular files directly to S3, Google Cloud Storage, or via HTTP.

How does Datamol handle 3D structures?

It provides a streamlined 'conformers' module to generate, minimize using force fields, cluster by RMSD, and visualize 3D molecular conformations.

What is the relationship between Datamol and RDKit?

Datamol is a high-level Pythonic wrapper for RDKit. It provides a more intuitive API and sensible defaults while remaining fully compatible with the RDKit ecosystem by returning native rdkit.Chem.Mol objects.

Datamol Cheminformatics

Name: Datamol Cheminformatics
Author: Microck

byMicrock

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Data Science & ML

Simplifies complex molecular informatics workflows by providing a Pythonic interface for RDKit with sensible defaults and built-in parallelization.

Datamol is a specialized Claude Code Skill designed to streamline molecular science and drug discovery tasks. It wraps the powerful RDKit library into a more accessible, high-level API, allowing developers and scientists to perform molecule standardization, property computation, and 3D conformer generation with minimal code. By abstracting complex RDKit operations into intuitive workflows, it enables efficient handling of large molecular datasets with native support for parallel processing and cloud-based file systems like S3 and GCS.

Key Features

01Automated 3D conformer generation, energy minimization, and analysis

02Advanced clustering, diversity selection, and Murcko scaffold analysis

03Simplified molecular format conversion and standardization (SMILES, InChI, SELFIES)

0481 GitHub stars

05Seamless I/O support for SDF, SMILES, CSV, and remote cloud storage

06High-performance batch computation of molecular descriptors and fingerprints

Use Cases

01Calculating molecular similarity and structural diversity for virtual screening

02Cleaning and standardizing large chemical datasets for machine learning models

03Generating 3D structures and calculating solvent accessible surface area (SASA) for drug discovery

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills datamol

For use in Claude.ai and ChatGPT

Download Skill