J. Drewe

Morgan fingerprints outperform physicochemical descriptors for scaffold-aware machine learning classification of β3-adrenergic receptor agonists

A reproducible, scaffold-aware ADRB3 agonist benchmark built from curated ChEMBL data and subtype-selectivity decoy controls is provided, showing that local structural environments encoded by ECFP4 fingerprints dominate predictive performance for ADRB3 agonists.