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

Summary

<p>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.</p> <p>The post <a href="https://www.marktechpost.com/2026/07/06/building-a-scaffold-split-random-forest-qsar-co-scientist-for-egfr-inhibitor-discovery-using-chembl-rdkit-shap-and-brics/">Building a Scaffold-Split Random Forest QSAR Co-Scientist for EGFR Inhibitor Discovery Using ChEMBL, RDKit, SHAP, and BRICS</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>