Towards Mechanistic QSAR Approaches for Predicting Reactive Oxygen Species (ROS) Generation: Mini Review

Reactive oxygen species (ROS) act as essential signalling mediators but become damaging when their generation exceeds the capacity of antioxidant defences. Predicting ROS-driven toxicity requires models that account for both the physicochemical drivers of radical formation and the biological pathways affected by oxidative stress. This review examines recent advances in mechanistic quantitative structure-activity relationship (QSAR) approaches for ROS prediction, highlighting descriptor systems that capture electrochemical reactivity, redox cycling behaviour, DNA alkylation potential and mitochondrial electron-leakage risk. Monte Carlo-optimised fragment descriptors developed using the CORAL platform are discussed for their ability to reveal substructural triggers of redox imbalance while retaining mechanistic transparency. Emerging multitarget nano-QSAR frameworks are considered for cases in which oxidative stress arises from converging mechanistic routes. The review also evaluates the strengths and limitations of current datasets, including inconsistencies between commonly used oxidative-stress assays, and outlines practical strategies for harmonising heterogeneous experimental outputs. Finally, it considers how mechanistic QSAR models can support regulatory evaluation through transparent hazard identification, grouping and read-across justification, as well as alignment with adverse outcome pathway frameworks, thereby moving the field toward more mechanistically grounded and regulatory-defensible tools for assessing ROS-mediated toxicity.