基于网络药理学与分子对接技术分析人参治疗卵巢癌的分子机制
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R285.5;R273

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国家自然科学基金资助项目(82374507)


Analysis of the Molecular Mechanisms of Ginseng Radix et Rhizoma for Ovarian Cancer Based on Network Pharmacology and Molecular Docking
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    摘要:

    目的:借助网络药理学与分子对接技术分析人参治疗卵巢癌的分子机制。方法:利用中药系统药理学数据库和分析平台(TCMSP)、SwissTargetPrediction 数据库筛选人参的活性成分和预测靶点。通过GeneCards、OMIM、PharmGKB数据库获取卵巢癌的疾病靶点。通过韦恩图获得人参活性成分预测靶点与卵巢癌疾病靶点的共同靶点。采用Cytoscape 3.9.1软件构建人参活性成分-卵巢癌靶点关系网络。借助STRING数据库构建蛋白质-蛋白质相互作用(PPI) 网络,并使用Cytoscape 3.9.1软件的CytoNCA插件进行网络拓扑学分析,筛选出核心靶点。借助DAVID数据库,对共同靶点进行基因本体(GO) 功能富集分析及京都基因与基因组百科全书(KEGG) 通路富集分析。采用分子对接技术(AutoDock Vina软件) 对人参活性成分与核心靶点的结合稳定性进行验证分析。结果:筛选得到人参活性成分22个(如山柰酚、β-谷甾醇)、预测靶点222个。通过活性成分预测靶点与卵巢癌疾病靶点的匹配分析,得到90个人参活性成分预测靶点与卵巢癌疾病靶点的共同靶点。通过PPI网络拓扑分析,最终确定13个核心靶点,包括丝氨酸/苏氨酸蛋白激酶B1(AKT1)、半胱氨酸天冬氨酸蛋白酶3(CASP3)、前列腺素内过氧化物合酶2(PTGS2)、肿瘤坏死因子(TNF) 等。GO功能富集分析结果显示,人参活性成分的核心靶点显著富集于缺氧应答、炎症调控、核受体信号转导相关生物学进程。KEGG通路富集分析结果显示,人参治疗卵巢癌的可能作用机制涉及163条信号通路。分子对接结果显示,13个核心靶点均可与人参活性成分有较好的结合活性,其中灌木远志酮A与PTGS2的结合亲和力最强。结论:人参可通过灌木远志酮A、山柰酚、人参皂苷Rh2等活性成分,作用于AKT1、CASP3、BCL2、TNF等核心靶点,调节多条信号通路,调控肿瘤细胞凋亡、炎症、转移等环节,发挥治疗卵巢癌的作用。

    Abstract:

    Abstract: Objective: To analyze the molecular mechanism of Ginseng Radix et Rhizoma for ovarian cancer through network pharmacology and molecular docking technology. Methods: The active ingredients and predicted target of Ginseng Radix et Rhizoma were selected from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction. The disease targets of ovarian cancer were obtained through GeneCards,OMIM,and PharmGKB. The common targets of the predicted targets of Ginseng Radix et Rhizoma active ingredients and ovarian cancer disease targets were obtained by Venn diagram. Cytoscape 3.9.1 software was used to construct the relationship network between Ginseng Radix et Rhizoma active ingredients and ovarian cancer targets. The protein-protein interaction (PPI) network was constructed with the help of the STRING,and the network topology analysis was performed using the CytoNCA plug-in of Cytoscape 3.9.1 software to screen out the core targets. By using DAVID,Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on common targets. The molecular docking technology (AutoDock Vina software) was used to verify and analyze the binding stability of Ginseng Radix et Rhizoma ingredients and core targets. Results: A total of 22 active ingredients (e. g., kaempferol, β -sitosterol) and 222 predict targets were identified. Through the matching analysis of active ingredient targets and ovarian cancer disease targets, 90 common targets of predicted targets of Ginseng Radix et Rhizoma active ingredients and ovarian cancer disease targets were obtained. Through PPI network topology analysis, 13 core targets were finally identified, including AKT serine/ threonine kinase 1( AKT1),cysteine-dependent aspartate-specific protease 3( CASP3),prostaglandin-endoperoxide synthase 2 (PTGS2),tumor necrosis factor (TNF),etc. The results of GO functional enrichment analysis showed that the core targets of Ginseng Radix et Rhizoma active ingredients were significantly enriched in biological processes related to hypoxia response, inflammation regulation, and nuclear receptor signal transduction. The results of KEGG pathway enrichment analysis showed that the possible mechanism of Ginseng Radix et Rhizoma in the prevention and treatment of ovarian cancer involved 163 signaling pathways. The results of molecular docking showed that all of the 13 core targets had good binding activity with the active ingredients of Ginseng Radix et Rhizoma, and the binding affinity of frutinone A and PTGS2 was the strongest. Conclusion: Ginseng Radix et Rhizoma can act on core targets such as AKT1,CASP3,BCL2,and TNF,and regulate multiple signaling pathways to regulate tumor cell apoptosis, inflammation,and metastasis through active ingredients such as frutinone A,kaempferol,and ginsenoside Rh2.

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何清,刘春曦,胡向丹.基于网络药理学与分子对接技术分析人参治疗卵巢癌的分子机制[J].新中医,2026,58(16):192-206

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  • 在线发布日期: 2026-08-23
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