Is the Medchem skill capable of processing large molecular datasets?

Yes, it is designed for scale and supports parallel processing (n_jobs) to handle high-throughput filtering of thousands of molecules simultaneously.

What is the Medchem Query Language?

It is a specialized syntax that allows users to combine multiple filtering criteria, such as 'rule_of_five AND NOT common_alerts', into a single logical expression.

How does this skill help with synthetic accessibility?

It provides complexity metrics like Bertz and Whitlock scores, allowing you to filter out molecules that may be too complex or difficult to synthesize.

Can I use Medchem to detect PAINS and other structural alerts?

Yes, Medchem includes filters for Pan-Assay Interference Compounds (PAINS), NIBR filters, and the Eli Lilly demerit system to flag problematic structural patterns.

What drug-likeness rules are supported by the Medchem skill?

The skill supports a wide range of established rules including Lipinski's Rule of Five, Veber, Oprea, CNS, Lead-like (soft and strict), Rule of Three, and Reos.

Medicinal Chemistry Toolkit

Name: Medicinal Chemistry Toolkit
Author: K-Dense-AI

byK-Dense-AI

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3,718

数据科学与机器学习

Filters and prioritizes molecular libraries using medicinal chemistry rules, structural alerts, and drug-likeness metrics.

关于

The Medchem skill provides a comprehensive suite of tools for molecular filtering and compound prioritization within drug discovery workflows. It enables developers and researchers to apply established medicinal chemistry rules—such as Lipinski's Rule of Five, Veber rules, and PAINS filters—to triage large compound libraries efficiently. By integrating structural alert detection, molecular complexity calculations, and custom property constraints, this skill helps identify lead-like candidates and flag potentially problematic functional groups before laboratory testing.

主要功能

Identify specific chemical groups, hinge binders, and reactive functional groups
Apply drug-likeness rules including Lipinski, Veber, CNS, and lead-like criteria
Calculate molecular complexity metrics (Bertz, Whitlock, Barone) for synthetic accessibility
3,718 GitHub stars
Advanced filtering using a specialized Medchem Query Language for complex logic
Detect structural alerts using PAINS, NIBR filters, and Lilly Demerits

使用场景

Detecting and filtering out reactive or interfering functional groups during lead discovery
Calculating and constraining molecular properties like TPSA, LogP, and molecular weight
High-throughput triage of large compound libraries to identify drug-like candidates

关于

主要功能

Identify specific chemical groups, hinge binders, and reactive functional groups
Apply drug-likeness rules including Lipinski, Veber, CNS, and lead-like criteria
Calculate molecular complexity metrics (Bertz, Whitlock, Barone) for synthetic accessibility
3,718 GitHub stars
Advanced filtering using a specialized Medchem Query Language for complex logic
Detect structural alerts using PAINS, NIBR filters, and Lilly Demerits

使用场景

Detecting and filtering out reactive or interfering functional groups during lead discovery
Calculating and constraining molecular properties like TPSA, LogP, and molecular weight
High-throughput triage of large compound libraries to identify drug-like candidates