Network Pharmacology and Computational Insights into PTGS2 Interactions with Apigenin and Genistein for Alzheimer's Disease Therapeutics

Abstract The present investigation provides a comprehensive analysis of the principal neuroactive phytochemicals and their molecular mechanisms of action in Bacopa monnieri , Centella asiatica , Curcuma longa , Mucuna pruriens , and Withania somnifera , all of which are traditionally recognized for their therapeutic potential in Alzheimer's disease. Phytochemical data were systematically retrieved from the IMPPAT database, followed by ADMET‐based screening, which yielded 14 candidate compounds for further analysis. Target prediction for these compounds was performed using SwissTargetPrediction and the STITCH database, leading to the identification of four lead phytochemicals (Apigenin, Kaempferol, Genstein, and Rosmarinic acid) based on their predicted interaction networks. Disease‐associated gene targets were extracted from the GEO and DisGeNET databases. Comparative mapping revealed 164 overlapping targets between the phytochemical and disease‐associated gene sets, which were subjected to functional enrichment analysis to elucidate their biological relevance. Network topology analysis was employed to identify central nodes within the protein‐protein interaction network, with the top five hub genes determined via betweenness centrality metrics. Molecular docking, followed by dynamics simulations, confirmed the strong binding affinity and conformational stability of apigenin and genistein with PTGS2, with docking scores of –8.07 kcal/mol and –7.59 kcal/mol, respectively. Additionally, the PTGS2‐genistein interaction exhibited superior dynamics.