What is the Medchem Query Language (MQL)?

MQL is a specialized query syntax that allows you to combine multiple filtering criteria (e.g., 'rule_of_five AND NOT common_alerts') into a single, readable string for complex triage.

Can this skill handle large molecular datasets?

Yes, MedChem is designed for scale and supports parallel processing (n_jobs) to efficiently filter datasets containing thousands of molecules.

Does it detect Pan-Assay Interference Compounds (PAINS)?

Yes, the skill includes specialized PAINS filters and structural alert systems like NIBR and Lilly Demerits to identify problematic scaffolds.

What drug-likeness rules are included in MedChem?

MedChem includes a comprehensive suite of rules including Lipinski's Rule of Five, Veber, Oprea, CNS-likeness, Lead-like (soft and strict), and Rule of Three.

MedChem Molecular Filtering

Name: MedChem Molecular Filtering
Author: Yezez9

byYezez9

0•

Data Science & ML

Applies medicinal chemistry rules, structural alerts, and drug-likeness filters to prioritize molecular libraries for drug discovery.

MedChem is a specialized cheminformatics skill designed to streamline molecular filtering and prioritization within drug discovery workflows. It provides Claude with the ability to apply established drug-likeness rules such as Lipinski's Rule of Five and Veber criteria, alongside advanced structural alert detection including PAINS, NIBR, and Lilly Demerits. By automating the triage of large compound libraries and calculating molecular complexity metrics, this skill helps researchers efficiently identify high-quality leads and avoid problematic functional groups early in the development process.

Key Features

01Extensive drug-likeness rule sets including Lipinski, Veber, and CNS rules

02Parallel processing capabilities for high-throughput library screening

03Molecular complexity and synthetic accessibility metric calculations

04Medchem Query Language (MQL) for complex, multi-criteria filtering

050 GitHub stars

06Sophisticated structural alert filtering for PAINS, NIBR, and Lilly Demerits

Use Cases

01Advanced lead optimization filtering using strict structural and property constraints

02Detection and removal of reactive or interfering functional groups in chemical datasets

03Initial triage of large compound libraries to identify drug-like candidates

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yezez9/research-agent medchem

For use in Claude.ai and ChatGPT