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medchem

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About medchem

M

medchem

Applies medicinal chemistry filters for compound triage

medchem is an agent skill for medicinal chemistry compound triage with the medchem Python library from datamol-io. It applies drug-likeness rules, such as Lipinski, Veber, CNS and lead-like rules, and structural alert catalogues, such as PAINS, NIBR and ChEMBL alerts. It also checks complexity thresholds against ZINC-derived values, detects functional groups and named substructure catalogues, and builds multi-criteria filters with a custom query language. Use it to triage compound libraries at scale, to prioritise compounds for hit-to-lead or lead optimisation work, or to filter molecules by structural alerts. The skill is clear that filters are context-specific guidelines, so their results should be combined with domain expertise and target knowledge rather than read as verdicts. The verified runtime is medchem 2.1.1, datamol 0.13.0 and RDKit 2026.3.6 on Python 3.11 or newer. The RuleFilters and structural classes return pandas DataFrames. Filters run locally, while installation and documentation lookups need a network connection. The Lilly native execution was not tested in that review.

View medchemAll AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/medchem