pendrin-qsar: An Open-Source QSAR Pipeline for Pendrin (SLC26A4) Inhibitors

An open-source cheminformatics and machine learning pipeline for pendrin (SLC26A4) inhibitors. Includes a curated dataset of 16 unique inhibitors across 6 scaffold classes, four QSAR models (Random Forest, XGBoost, Ridge, PLS) validated by LOO-CV, Y-scrambling, applicability domain analysis, and conformal prediction, plus virtual screening of 13 novel benzofuran analogs. Top predicted virtual screening hit: V-2F4Cl (predicted IC50 = 0.86 µM, 80% CI: 0.43-1.73 µM). Code runs in a single click in Google Colab with no installation required. GitHub: https://github.com/drjoykarmakar/pendrin-qsar