Integrated Computational Analysis of Antioxidant Compounds: Targeting the 𝐾𝑒𝑎𝑝۱–𝑁𝑟𝑓۲ Pathway for Enhanced Therapeutic Potential

Oxidative stress plays a critical role in various pathologies, necessitating the development of potent Keap۱ inhibitors. This study addresses the research gap by employing a comprehensive computational approach to identify novel Keap۱ inhibitors from a library of ۶۱ antioxidant compounds obtained from PubChem. Molecular docking simulations, ADMET property prediction, Density Functional Theory (DFT) calculations, and QSAR analysis were utilized. Three compounds (۸, ۳۳, and ۵۸) were selected based on their significantly superior MolDock scores (-۱۳۸.۹۱۴, -۱۶۹.۹۰۲, and -۱۳۴.۷۹۸ kcal/mol, respectively) compared to Ascorbic acid (-۷۷.۳۶۶ kcal/mol), indicating strong binding affinities. These compounds exhibited high stability through hydrogen bonds and hydrophobic interactions with key Keap۱ residues. ADMET analyses confirmed favorable drug-like properties and safety profiles, suggesting potential for combination therapy. DFT calculations provided insights into their electronic properties, including HOMO, LUMO, and energy gap values, while molecular electrostatic potential maps illustrated charge density distributions relevant to biological activity. QSAR analysis highlighted differences in physicochemical properties, indicating varied therapeutic potential. Overall, these findings support the development of effective antioxidant therapies for oxidative stress-related conditions.

کلیدواژه ها:

Molecular docking ، oxidative stress ، pharmacokinetics ، DFT studies ، QSAR Analysis