Medicinal Chemistry Toolkit

关于

The Medchem skill equips AI coding agents with the capability to perform advanced chemoinformatics tasks using the medchem Python library. It enables the automated application of industry-standard molecular filters—including Lipinski's Rule of Five, Veber rules, and PAINS filters—to efficiently triage compound libraries. By integrating structural alert detection, molecular complexity calculations, and a specialized query language, this skill helps developers and researchers identify high-quality drug candidates, detect problematic functional groups, and streamline lead optimization workflows within a medicinal chemistry context.

主要功能

• 8 GitHub stars
• Calculate molecular complexity and synthetic accessibility metrics
• Identify specific chemical groups and reactive functional moieties
• Apply drug-likeness rules like Lipinski, Veber, and CNS guidelines
• Utilize a specialized Medchem Query Language for complex filtering logic
• Detect PAINS patterns and structural alerts (NIBR, Lilly Demerits)

使用场景

• High-throughput screening and initial triage of large compound libraries
• Lead optimization filtering using strict medicinal chemistry criteria
• Automated identification of toxic or reactive structural patterns in chemical datasets