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Background Hypertension is a leading risk factor for disability and deaths worldwide. Evidence indicates that alpha-mangostin(α-MG) can reduce blood pressure and improve target organ damage. Nonetheless, its pharmacological targets and potential mechanisms of action remain inadequately elucidated. Method We used SwissTargetPrediction to identify α-MG’s drug targets and DisGeNET, GeneCards, CTD, and GEO databases for hypertension-related targets, and then determined antihypertensive therapeutic targets of α-MG by intersecting these targets. GO functional enrichment analysis, KEGG pathway analysis, and disease association analysis were conducted using the DAVID database and R package “clusterprofile”, visualized with Cytoscape software. The binding affinity of α-MG to identified targets was confirmed through molecular docking using Autodock Vina v.1.2.2 software. The impact of α-MG on target genes was validated using an Angiotensin II-induced hypertensive mouse model and RT-qPCR. Results A total of 51 potential antihypertensive therapeutic targets for α-MG were identified by intersecting 109 drug targets with 821 disease targets. Furthermore, 10 cellular component terms, 10 disease terms, and the top 20 enriched biological processes, molecular functions, and KEGG pathways related to α-MG’s antihypertensive effects were documented. Molecular docking studies indicated a strong binding affinity of α-MG with the HSP90AA1 domain. In Ang II-induced hypertensive mice aorta, treatment with α-MG effectively reversed the aberrant mRNA expression of TNF, HSP90AA1, NFKB1, PPARG, SIRT1, PTGS2, and RELA. Conclusion Our analyses showed that TNF, HSP90AA1, NFKB1, PPARG, SIRT1, PTGS2, and RELA might be α-MG’s potential therapeutic targets for hypertension, laying groundwork for further investigation into its pharmacological mechanisms and clinical uses.
Background Hypertension is a leading risk factor for disability and deaths worldwide. Evidence indicates that alpha-mangostin(α-MG) can reduce blood pressure and improve target organ damage. Nonetheless, its pharmacological targets and potential mechanisms of action remain inadequately elucidated. Method We used SwissTargetPrediction to identify α-MG’s drug targets and DisGeNET, GeneCards, CTD, and GEO databases for hypertension-related targets, and then determined antihypertensive therapeutic targets of α-MG by intersecting these targets. GO functional enrichment analysis, KEGG pathway analysis, and disease association analysis were conducted using the DAVID database and R package “clusterprofile”, visualized with Cytoscape software. The binding affinity of α-MG to identified targets was confirmed through molecular docking using Autodock Vina v.1.2.2 software. The impact of α-MG on target genes was validated using an Angiotensin II-induced hypertensive mouse model and RT-qPCR. Results A total of 51 potential antihypertensive therapeutic targets for α-MG were identified by intersecting 109 drug targets with 821 disease targets. Furthermore, 10 cellular component terms, 10 disease terms, and the top 20 enriched biological processes, molecular functions, and KEGG pathways related to α-MG’s antihypertensive effects were documented. Molecular docking studies indicated a strong binding affinity of α-MG with the HSP90AA1 domain. In Ang II-induced hypertensive mice aorta, treatment with α-MG effectively reversed the aberrant mRNA expression of TNF, HSP90AA1, NFKB1, PPARG, SIRT1, PTGS2, and RELA. Conclusion Our analyses showed that TNF, HSP90AA1, NFKB1, PPARG, SIRT1, PTGS2, and RELA might be α-MG’s potential therapeutic targets for hypertension, laying groundwork for further investigation into its pharmacological mechanisms and clinical uses.
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