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rdkit

Perform cheminformatics analysis with RDKit for molecular I/O, descriptors, fingerprints, and substructure searches.

94|11|Updated Mar 26, 2026
Search Tags:#cheminformatics#drug-discovery#fingerprints#substructure#descriptors#rdkit
One-click install
npx skills add https://github.com/swaruplab/operon --skill rdkit-swaruplab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rdkit
Source: https://github.com/swaruplab/operon/tree/main/src-tauri/protocols/rdkit
Command: npx skills add https://github.com/swaruplab/operon --skill rdkit-swaruplab

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

RDKit provides a comprehensive, programmable toolkit for cheminformatics in Python, enabling precise molecular I/O, descriptor calculation, fingerprinting, substructure searching, and 2D/3D coordinate handling within automated workflows. It supports advanced sanitization and custom algorithms beyond higher-level wrappers.

Core Features & Use Cases

  • Molecular I/O & Creation: Read/write SMILES, SDF/MOL, InChI, and create Mol objects for downstream analysis.
  • Descriptors & Properties: Compute molecular weight, logP, TPSA, hydrogen bond donors/acceptors, ring counts, and related properties.
  • Fingerprints & Similarity: Generate Morgan/topological fingerprints and measure Tanimoto similarity for library screening.
  • Substructure Searching: Use SMARTS patterns to identify functional groups and motifs across datasets.
  • 2D/3D Coordinates & Conformers: Generate coordinates, optimize conformers, and align molecules to templates.
  • Reactions & Transformations: Define reaction SMARTS and apply transformations to reactants and products.
  • Use Case: In lead discovery, screen a chemical library to identify close analogs to a target scaffold and extract matched substructures for SAR analysis.

Quick Start

Install RDKit and run the provided scripts to load molecules, compute descriptors, and perform similarity searches.

Frequently Asked Questions about rdkit

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

FAQPage Schema
How do I compute molecular descriptors and fingerprints in Python for drug discovery?▼

Substructure searching in cheminformatics uses SMARTS patterns to identify functional groups and motifs across datasets. RDKit enables this by creating Mol objects from input molecules and applying SMARTS queries to extract matched substructures for SAR analysis.

Can I generate 2D and 3D molecular coordinates and conformers with RDKit?▼

Yes, you can generate 2D and 3D molecular coordinates and conformers with RDKit. The skill provides APIs to generate coordinates, optimize conformers, and align molecules to templates for structural analysis in discovery workflows.

What is the best way to measure molecular similarity for chemical library screening?▼

The best way to measure molecular similarity for chemical library screening is generating Morgan or topological fingerprints and computing Tanimoto similarity. RDKit provides programmatic APIs to perform this fingerprint-based similarity analysis on datasets.

Does this cheminformatics skill support defining and applying chemical reactions?▼

Yes, this cheminformatics skill supports chemical reactions. You can define reaction SMARTS and apply transformations to reactants and products, enabling programmatic reaction handling within automated molecular discovery workflows.

Do I need the RDKit library installed to run molecular I/O and sanitization workflows?▼

Yes, you need the RDKit library installed to run molecular I/O and sanitization workflows. The skill's core requirements are the RDKit library and the accompanying scripts and reference guides that enable reading, writing, and sanitizing molecular structures.

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