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TNF-centered network pharmacology and molecular modeling of selected Andrographis paniculata compounds in
Sefren Geiner Tumilaar1, Maulida Mazaya2
1Research Center for Computing, Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Cibinong Science Center, Cibinong, 16911, Indonesia.
Abstract:
Hypertension is increasingly recognized as an inflammatory-associated cardiovascular disorder in which cytokine-mediated endothelial dysfunction plays a central role. Tumor necrosis factor (TNF) is a key regulator linking oxidative stress, vascular inflammation, and blood pressure dysregulation, making it a potential therapeutic target. Andrographis paniculata, a medicinal plant rich in bioactive diterpenoids and flavonoids, has suggested cardiovascular benefits, although its molecular mechanisms remain insufficiently defined. In this study, an integrated computational strategy was employed to explore the potential molecular basis of TNF-centered interaction of A. paniculata compounds. Network pharmacology analysis identified TNF, IL6, and TP53 as central hubs within the hypertension-associated protein interaction network, highlighting the involvement of inflammatory signaling pathways. Among the investigated compounds, neoandrographolide emerged as a promising candidate for TNF-associated interactions under the applied computational conditions, supported by favorable binding affinity and stable ligand-target protein interactions. Molecular dynamics simulations further indicated that the neoandrographolide-TNF complex maintained structural stability, persistent hydrogen bonding, and energetically favorable interactions throughout the simulation period, suggested stable binding behavior under dynamic conditions. These findings suggest that TNF may represent a potential candidate target associated with the predicted antihypertensive activity of selected A. paniculata compounds, potentially contributing to the modulation of endothelial dysfunction and vascular inflammation associated with hypertension. These findings are based on computational predictions and require experimental validation. Overall, this study provides computational insights into the potential anti-inflammatory effects of A. paniculata, highlighting TNF as candidate pharmacological axis and supporting future experimental validation toward cytokine-targeted antihypertensive strategies.
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