What Python libraries are required for this skill?

The skill requires the 'chembl_webresource_client' package to communicate with the ChEMBL API.

Does this skill support chemical structure searches?

Yes, it supports similarity and substructure searches using SMILES strings to identify compounds with similar chemical architectures.

Is the bioactivity data normalized?

ChEMBL provides a 'pchembl_value' which is a normalized -log scale of activity values, making it easier to compare potency across different assays.

What is the ChEMBL database skill used for?

It is used to programmatically access the ChEMBL database to find bioactive molecules, retrieve experimental activity data like IC50, and search for protein target information.

Can I export ChEMBL data to other formats?

Yes, the skill provides patterns to convert query results into pandas DataFrames, which can then be exported to CSV, Excel, or used for further data analysis.

ChEMBL Database & Drug Discovery

Name: ChEMBL Database & Drug Discovery
Author: K-Dense-AI

byK-Dense-AI

•

3,719

Data Science & ML

Queries the ChEMBL database to retrieve bioactive molecule data, drug targets, and bioactivity measurements for medicinal chemistry.

About

This skill integrates ChEMBL's vast repository of bioactive molecules and drug discovery data directly into Claude's workflow. It allows researchers and developers to programmatically search over 2 million compounds, retrieve bioactivity measurements like IC50 and Ki, and explore target-ligand interactions. By providing specialized patterns for the ChEMBL Python client, it facilitates complex tasks such as structure-activity relationship (SAR) studies, similarity searches via SMILES, and the analysis of FDA-approved drug mechanisms, making it an essential tool for cheminformatics and early-stage drug discovery.

Key Features

3,719 GitHub stars
Advanced structure searches including similarity and substructure matching
Compound searching by name, structure (SMILES), or chemical properties
Biological target identification for proteins, enzymes, and clinical markers
Comprehensive drug information including mechanisms of action and indications
Bioactivity data retrieval for IC50, Ki, EC50, and other potency measurements

Use Cases

Identifying and ranking potent inhibitors for specific protein targets like kinases
Mapping approved drugs to their biological targets for drug repurposing research
Conducting SAR studies by analyzing the bioactivity of structurally similar molecular scaffolds

About

Key Features

3,719 GitHub stars
Advanced structure searches including similarity and substructure matching
Compound searching by name, structure (SMILES), or chemical properties
Biological target identification for proteins, enzymes, and clinical markers
Comprehensive drug information including mechanisms of action and indications
Bioactivity data retrieval for IC50, Ki, EC50, and other potency measurements

Use Cases

Identifying and ranking potent inhibitors for specific protein targets like kinases
Mapping approved drugs to their biological targets for drug repurposing research
Conducting SAR studies by analyzing the bioactivity of structurally similar molecular scaffolds