Mechanism of mangiferin in the treatment of oral submucous fibrosis based on Gene Expression Omnibus database chip mining combined with network pharmacology and molecular docking.

Ziyi Song, Chao Yang, Yunlong Zhang, Zhujiang Zhang, Tianjiao Ren, Xinyue Zhang, Xue Li
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Abstract

Objectives: This study aims to investigate the primary target and potential mechanism of mangiferin (MF) in treating oral submucous fibrosis (OSF) through Gene Expression Omnibus (GEO) database chip mining, network pharmacology, and molecular docking techniques.

Methods: Potential therapeutic targets for OSF were identified using GEO chip data. The potential targets of MF were predicted, and disease-related targets for OSF were collected from databases. A Venn diagram was created using the EVenn platform to identify overlapping targets. The protein-protein interaction (PPI) network was constructed using the STRING database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the DAVID platform. Cytoscape 3.10.1 software was used to visualize a drug-target-pathway-disease network, while AutoDocktools 1.5.6 software was employed for molecular docking analysis.

Results: A total of 356 potential targets for MF and 360 disease-related targets for OSF were obtained from multiple databases. The top 15 key target proteins in the PPI network were selected as significant candidates. GO function and KEGG pathway enrichment analyses revealed that MF treatment primarily involved advanced glycation end products-receptor (AGE-RAGE), epidermal growth factor receptor (EGFR), and other signaling pathways associated with OSF pathogenesis. Molecular docking analysis demonstrated that MF exhibited a strong binding activity toward AKT serine kinase 1 (AKT1), tumor necrosis factor (TNF), and other core targets.

Conclusions: These findings suggest that MF may exert its therapeutic effects on OSF through a multitarget approach involving various signaling pathways.

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基于基因表达总库数据库芯片挖掘结合网络药理学和分子对接的芒果苷治疗口腔黏膜下纤维化的机制。
研究目的本研究旨在通过基因表达总库(GEO)数据库芯片挖掘、网络药理学和分子对接技术,研究芒果苷(MF)治疗口腔黏膜下纤维化(OSF)的主要靶点和潜在机制:方法:利用 GEO 芯片数据确定 OSF 的潜在治疗靶点。方法:利用 GEO 芯片数据确定 OSF 的潜在治疗靶点,预测 MF 的潜在靶点,并从数据库中收集 OSF 的疾病相关靶点。利用 EVenn 平台绘制了维恩图,以确定重叠的靶点。利用 STRING 数据库构建了蛋白质-蛋白质相互作用(PPI)网络。使用 DAVID 平台进行了基因本体(GO)和京都基因组百科全书(KEGG)富集分析。Cytoscape 3.10.1软件用于药物-靶点-途径-疾病网络的可视化,AutoDocktools 1.5.6软件用于分子对接分析:结果:从多个数据库中共获得了 356 个中风的潜在靶点和 360 个 OSF 的疾病相关靶点。PPI网络中前15个关键靶蛋白被选为重要候选靶蛋白。GO功能和KEGG通路富集分析显示,MF治疗主要涉及晚期糖化终产物受体(AGE-RAGE)、表皮生长因子受体(EGFR)和其他与OSF发病机制相关的信号通路。分子对接分析表明,MF对AKT丝氨酸激酶1(AKT1)、肿瘤坏死因子(TNF)和其他核心靶点具有很强的结合活性:这些研究结果表明,MF 可通过涉及各种信号通路的多靶点方法对 OSF 发挥治疗作用。
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