rdkit

Analyze and manipulate molecular structures with RDKit cheminformatics operations.

557|98|Updated Nov 7, 2025
One-click install
npx skills add https://github.com/jimmc414/Kosmos --skill rdkit-jimmc414
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rdkit
Source: https://github.com/jimmc414/Kosmos/tree/main/kosmos-claude-scientific-skills/scientific-skills/rdkit
Command: npx skills add https://github.com/jimmc414/Kosmos --skill rdkit-jimmc414

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill empowers chemists and researchers by providing a powerful toolkit for molecular analysis, manipulation, and visualization, streamlining cheminformatics workflows.

Core Features & Use Cases

  • Molecular Manipulation: Read, write, sanitize, and modify molecular structures from various formats (SMILES, MOL, SDF).
  • Property Calculation: Compute a wide range of molecular descriptors like molecular weight, LogP, TPSA, and hydrogen bond donors/acceptors.
  • Fingerprinting & Similarity: Generate various molecular fingerprints (Morgan, MACCS) and calculate similarity scores for screening and clustering.
  • Substructure Searching: Identify specific chemical substructures using SMARTS patterns.
  • 2D/3D Generation & Visualization: Create 2D depictions and 3D conformers, and visualize molecules with customizable options.
  • Use Case: A medicinal chemist can use this Skill to quickly calculate Lipinski's Rule of Five parameters for a list of drug candidates, filter them based on desired substructures, and visualize the most promising ones.

Quick Start

Use the rdkit skill to calculate the molecular weight and LogP for the SMILES string 'CCO'.

Frequently Asked Questions about rdkit

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

FAQPage Schema
How do I calculate molecular descriptors like LogP and TPSA from a SMILES string?

Calculate molecular descriptors by parsing SMILES strings to compute physicochemical properties like LogP, TPSA, molecular weight, and hydrogen bond donor/acceptor counts. This streamlines cheminformatics workflows for drug discovery.

Can I perform substructure searches using SMARTS patterns across a list of molecules?

You can perform substructure searches using SMARTS patterns to identify specific chemical substructures across molecular datasets. This allows you to filter drug candidates and retain only molecules matching your desired structural features.

What's the best way to generate Morgan fingerprints and calculate molecular similarity scores?

Generate Morgan or MACCS fingerprints from molecular structures and calculate their similarity scores to facilitate molecular screening and clustering. This helps identify promising drug candidates by comparing structural features.

Does this approach support reading and writing multiple molecular formats like SDF and MOL?

Yes, this approach supports reading, writing, sanitizing, and modifying molecular structures from various formats including SDF, MOL, and SMILES. This enables fine-grained control over molecular data manipulation in computational chemistry workflows.

How do I generate 2D depictions and 3D conformers for molecular visualization?

Generate 2D depictions and 3D conformers by creating molecular visualizations with customizable options from your input structures. This allows you to visually inspect the most promising drug candidates during your drug discovery research.

Can I evaluate drug candidates by calculating Lipinski's Rule of Five parameters?

You can evaluate drug candidates by calculating Lipinski's Rule of Five parameters such as molecular weight, LogP, and hydrogen bond donors/acceptors. This allows you to quickly filter lists of drug candidates and visualize the most promising ones.