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MedChem

Maintainer K-Dense Inc. · Last updated April 1, 2026

Medchem is a Python library for molecular filtering and prioriti.

Claude CodeOpenClawNanoClawAnalysisReproductionmedchemchemistrypackagecheminformatics & drug discovery

Original source

K-Dense-AI/claude-scientific-skills

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/medchem

Maintainer
K-Dense Inc.
License
Apache-2.0 license
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • Medchem is a Python library for molecular filtering and prioritization in drug discovery workflows. Apply hundreds of well-established and novel molecular filters, structural alerts, and medicinal chemistry rules to efficiently triage and prioritize compound libraries at scale. Rules and filters are context-specific—use as guidelines combined with domain expertise.
  • smiles = "CC(=O)OC1=CC=CC=C1C(=O)O" # Aspirin passes = mc.rules.basic_rules.rule_of_five(smiles).

Source Doc

Excerpt From SKILL.md

When to Use This Skill

This skill should be used when:

  • Applying drug-likeness rules (Lipinski, Veber, etc.) to compound libraries
  • Filtering molecules by structural alerts or PAINS patterns
  • Prioritizing compounds for lead optimization
  • Assessing compound quality and medicinal chemistry properties
  • Detecting reactive or problematic functional groups
  • Calculating molecular complexity metrics

1. Medicinal Chemistry Rules

Apply established drug-likeness rules to molecules using the medchem.rules module.

Available Rules:

  • Rule of Five (Lipinski)
  • Rule of Oprea
  • Rule of CNS
  • Rule of leadlike (soft and strict)
  • Rule of three
  • Rule of Reos
  • Rule of drug
  • Rule of Veber
  • Golden triangle
  • PAINS filters

Single Rule Application:

import medchem as mc

## Check specific rules

passes_oprea = mc.rules.basic_rules.rule_of_oprea(smiles)
passes_cns = mc.rules.basic_rules.rule_of_cns(smiles)
python
import datamol as dm
import medchem as mc

Use cases

  • Applying drug-likeness rules (Lipinski, Veber, etc.) to compound libraries.
  • Filtering molecules by structural alerts or PAINS patterns.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

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