Warfarin derivatives as free radical scavengers: a coumarin scaffold-based linear regression model with in vitro...

Antioxidant agents that efficiently scavenge reactive oxygen species (ROS) are of great interest in medicinal chemistry for their potential to mitigate oxidative stress-related pathologies. In this work, we developed an interpretable Multiple Linear Regression (MLR) QSAR model using seven molecular descriptors (D/Dr05, MATS2v, MATS8p, Mor24m, L2s, HATS3u, H8m) to predict the free radical scavenging activity of coumarin-based compounds as measured by the IC₅₀ in the DPPH assay. The MLR-QSAR model showed strong goodness-of-fit and robust internal and external validation parameters (r² = 81.04, Q²_LOO = 77.93, Q²_boot = 76.78, r²_ext = 75.38, y_scrambler² = 0.25), supporting its predictive reliability. We applied the model to predict the antiradical potential of a novel set of Warfarin derivatives, a class of molecules historically known for anticoagulant properties but with unexplored antioxidant potential. Experimental in vitro DPPH assays on the seven Warfarin derivatives (WD) revealed a positive correlation (r = 0.63) with the predictions, validating the MLR-QSAR as a screening tool. Furthermore, all WD exhibited significant DPPH radical scavenging activity, demonstrating the chemical antioxidant potential of an anticoagulant-derived scaffold. This dual in silico-in vitro strategy highlights the value of interpretable QSAR models for guiding compound prioritization and structural optimization towards new coumarin-based antioxidants.