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.