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[ARTICLE · art-48744] src=marktechpost.com ↗ pub= topic=artificial-intelligence verified=true sentiment=· neutral

Building a Scaffold-Split Random Forest QSAR Co-Scientist for EGFR Inhibitor Discovery Using ChEMBL, RDKit, SHAP, and BRICS

A tutorial demonstrates building an autonomous AI co-scientist for EGFR C797S inhibitor discovery using ChEMBL, RDKit, SHAP, and BRICS. The system mines IC50 data, trains a scaffold-split Random Forest QSAR model, interprets potency drivers with SHAP, and generates novel candidates via BRICS fragment recombination.

read1 min views1 publishedJul 7, 2026

In this tutorial, we build an autonomous AI co-scientist for EGFR C797S inhibitor discovery. We resolve the target through ChEMBL and UniProt, then mine IC50 records into a clean pIC50 dataset. We use RDKit to standardize molecules, compute Morgan fingerprints, and train a scaffold-split Random Forest QSAR model. We interpret potency drivers with SHAP, then recombine BRICS fragments to generate and rank novel candidates.

The post Building a Scaffold-Split Random Forest QSAR Co-Scientist for EGFR Inhibitor Discovery Using ChEMBL, RDKit, SHAP, and BRICS appeared first on MarkTechPost.

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