EGFR and CYP signaling disruption underlies 6PPD-quinone hepatotoxicity: Insights from a network and machine learning approach

N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-quinone), an emerging environmental contaminant derived from the common tire additive 6PPD, has been alarmingly detected in human biology samples and is associated with liver injury. However, the underlying molecular mechanisms driving its hepatotoxicity remain largely unexplored. We employed an integrated in silico strategy encompassing ADMET profiling, network toxicology analysis, molecular docking, molecular dynamics (MD) simulations, and machine learning (ML) to uncover the hepatotoxic mechanisms of 6PPD-quinone. Our analysis identified 62 critical intersection genes between 6PPD-quinone targets and hepatotoxicity-related genes. Protein-protein interaction analysis revealed two distinct functional modules: Epidermal Growth Factor Receptor (EGFR)-mediated signaling pathways and Cytochrome P450 (CYP) enzyme-driven metabolic processes. Molecular docking and MD simulations confirmed remarkably strong and stable binding interactions between 6PPD-quinone and EGFR. An advanced ML model further classified 6PPD-quinone as a potent EGFR inhibitor, achieving a validation accuracy of 0.90 and an F1-score of 0.90. Comprehensive ADMET and docking analyses additionally indicated multi-CYP enzyme inhibition capabilities. In conclusion, our findings suggest that 6PPD-quinone induces liver injury through a dual mechanism involving EGFR signaling suppression and CYP-mediated metabolic disruption. This work provides a critical mechanistic framework for assessing the hepatotoxic risks of tire-derived environmental pollutants and highlights potential intervention targets for mitigating their adverse health effects.