Computational Evaluation of Natural Polyphenols from Cistus creticus as Multitarget Antioxidants: Docking, PASS Prediction, and Pharmacokinetic Study

Oxidative stress plays a central role in the pathogenesis of numerous chronic diseases, prompting the search for effective natural antioxidants with multitarget mechanisms of action. In this study, bioactive polyphenolic compounds identified from Cistus creticus were investigated using an integrated in silico approach combining molecular docking, PASS prediction, and ADMET analysis. Molecular docking was performed against the Keap1 protein (PDB ID: 2FLU) and the p22phox (PDB ID: 7YXW), two key regulators of oxidative stress. The results demonstrated strong binding affinities for most flavonoids, particularly hesperidin, quercetin, rutin, and their derivatives, which formed stable hydrogen bond interactions with critical amino acid residues involved in protein function. PASS prediction further supported these findings, revealing high probabilities of antioxidant activity (Pa > 0.7) for the majority of compounds, especially myricetin, rutin, and quercetin derivatives. ADMET profiling indicated favorable safety characteristics for all compounds, including the absence of mutagenicity and hepatotoxicity, although glycosylated flavonoids showed limited permeability and potential P-glycoprotein efflux. Overall, the results suggest that polyphenolic compounds derived from Cistus creticus exhibit promising antioxidant potential through a dual mechanism involving activation of the Nrf2 signaling pathway and inhibition of reactive oxygen species production via the NADPH oxidase. This study highlights the relevance of integrating computational approaches to identify and optimize natural compounds as potential therapeutic agents against oxidative stress-related disorders.