<![CDATA[Hexacyclinic acid has shown promising pharmacological activities, yet its molecular mechanisms and therapeutic potential remain largely unexplored. This study aimed to identify potential disease targets and elucidate the mechanism of action of hexacyclinic acid using an integrated computational approach. We employed network pharmacology analysis to predict potential targets and pathways of hexacyclinic acid using SuperPred and Swiss Target server, followed by protein-protein interaction network construction via STRING database. Pathway enrichment analysis was performed using ShyniGO and DAVID databases. Molecular docking studies were conducted using AutoDock Vina to evaluate binding affinities between hexacyclinic acid and identified target proteins. Binding poses and interactions were visualized using Biovia Discovery Studio Visualizer. Disease prediction analysis identified osteoarthritis as the most promising target, with the IL-17 signaling pathway emerging as the most significant KEGG pathway. TNF-α and IL-1β were identified as key molecular targets within this pathway. Molecular docking simulations corroborated these findings, revealing favorable binding energies between hexacyclinic acid and TNF-α (-8.62 kcal/mol) and IL-1β (-8.76 kcal/mol). These results suggest that hexacyclinic acid may exert its anti-osteoarthritis effects by modulating the IL-17 signaling pathway, particularly through interactions with TNF-α and IL-1β. The strong binding affinities observed indicate a potentially high efficacy of hexacyclinic acid in targeting these inflammatory mediators. These results have significant clinical implications, potentially leading to the development of new therapeutic strategies for osteoarthritis management with reduced side effects compared to current treatments. Future research should focus on experimental validation through in vitro and in vivo models to confirm these computational predictions and establish hexacyclinic acid as a viable candidate for clinical development]]>
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