Generate molecular fingerprints and visualize molecules using modern RDKit APIs.
npx skills add https://github.com/mcox3406/claude-comp-chem-skills --skill rdkit-mcox3406
Please help me install this Agent Skill. Skill: rdkit Source: https://github.com/mcox3406/claude-comp-chem-skills/tree/main/rdkit Command: npx skills add https://github.com/mcox3406/claude-comp-chem-skills --skill rdkit-mcox3406
This Skill provides up-to-date RDKit syntax and patterns, overcoming the common issue of outdated information often found in LLM training data, ensuring accurate cheminformatics operations.
rdFingerprintGenerator for fingerprints and MolDraw2D for molecule visualization.Use the rdkit skill to convert the SMILES string 'CCO' into an RDKit molecule object.
High-intent search queries and answers about installing and using this skill.
To generate Morgan fingerprints from SMILES strings, parse the SMILES into a molecule object and use the modern rdFingerprintGenerator module to compute the fingerprint vectors for cheminformatics similarity analysis.
Calculating Tanimoto similarity in RDKit involves generating molecular fingerprints for your target structures and then computing the pairwise similarity scores between those fingerprint vectors to identify closely related chemical compounds.
To draw and visualize molecules from SMILES, convert the string to a molecule object and utilize the MolDraw2D API, which provides up-to-date rendering capabilities for generating 2D chemical structure depictions.
RDKit cheminformatics code uses deprecated functions when relying on outdated API patterns; modern implementations require switching to the rdFingerprintGenerator module to ensure accurate and supported fingerprint generation.
Yes, you can calculate molecular property descriptors and perform substructure searches by parsing your SMILES into molecule objects, then utilizing RDKit's built-in functions for property computation and structural querying.
InternScienceGenerate novel SMILES strings with optional Lipinski and preset filtering using REINVENT4 de novo model.
ovachieverConvert SMILES or RDKit molecules into ML-ready numerical representations.
JosephWoodallCompute molecular descriptors, fingerprints, and substructure searches with RDKit in Python.
InternScienceCompute molecular structure complexity metrics for SMILES lists.