[1]偶勇,古娜,晁旭.基于网络药理学探讨黄芪-莪术治疗肝癌的作用机制[J].西部中医药,2026,39(01):129-134.[doi:10.12174/j.issn.2096-9600.2026.01.21]
　OU Yong,GU Na,CHAO Xu.Network Pharmacology-based Exploration into the Mechanism of Huangqi-Ezhu in Treating Liver Cancer[J].Western Journal of Traditional Chinese Medicine,2026,39(01):129-134.[doi:10.12174/j.issn.2096-9600.2026.01.21]
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基于网络药理学探讨黄芪-莪术治疗肝癌的作用机制()

《西部中医药》[ISSN:2096-9600/CN:62-1204/R]

卷:
39
期数:
2026年01期
页码:
129-134
栏目:
二次研究
出版日期:
2026-01-15

文章信息/Info

Title:
Network Pharmacology-based Exploration into the Mechanism of Huangqi-Ezhu in Treating Liver Cancer
作者:
偶勇1,2, 古娜2, 晁旭3
1.陕西中医药大学，陕西 咸阳 712000
2.南郑区人民医院，陕西 汉中 723100
3.陕西中医药大学第二附属医院,陕西 咸阳 712000
Author(s):
OU Yong1,2, GU Na2, CHAO Xu3
1.Shaanxi University of Chinese Medicine, Xianyang 712000, China
2.Nanzheng District People’s Hospital, Hanzhong 723100, China
3.The Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
关键词:
肝癌; 黄芪-莪术; 网络药理学; 作用机制
Keywords:
liver cancer; network pharmacology; mechanism
分类号:
R273
DOI:
10.12174/j.issn.2096-9600.2026.01.21
文献标志码:
A
摘要:
目的采用网络药理学和分子对接方法探索黄芪-莪术药对治疗肝癌的作用靶点以及相关信号通路，研究其潜在机制。 方法通过中药系统药理学数据库与分析平台（traditional Chinese medicine systems pharmacolog，TCMSP）和GeneCards、OMIM、DrugBank数据库分别筛选出黄芪-莪术和肝癌的作用靶点；运用Venny 2.1.0对药物和肝癌靶点进行匹配；应用STRING平台构建蛋白-蛋白相互作用（protein-protein interaction，PPI）网络；导入Cytoscape软件，利用CytoHubba筛选核心靶点；将预测靶点应运Metascape数据库进行GO富集和KEGG通路分析。 结果获得黄芪-莪术共23个活性成分、188个靶点，与肝癌相互作用靶点共104个。GO富集分析获得150条生物过程（biological Process，BP）、57条细胞成分（cellular component，CC）、95条分子功能（molecular function，MF）；KEGG通路分析获得168条信号通路。 结论黄芪-莪术通过多成分、多靶点、多通路治疗肝癌。
Abstract:
ObjectiveTo explore the targets and the relevant signaling pathway of Huangqi (Astragali radix)-Ezhu (Curcumae rhizoma) in the treatment of liver cancer using network pharmacology and molecular docking, and to study its potential mechanism. MethodsThe targets of action of Huangqi-Ezhu and liver cancer were screened out respectively from TCMSP, GeneCards, OMIM and DrugBank, and the common targets between the medicine and liver cancer were identified using Venny 2.1.0; STRING platform was employed to build PPI network; the core targets were identified using CytoHubba after being imported into Cytoscape; the Metascape database was utilized to perform GO enrichment and KEGG pathway analysis on the predicted targets. ResultsAll 23 active ingredients, 188 targets from Huangqi-Ezhu, and 104 targets interacting with liver cancer were identified in the study. GO enrichment analysis revealed 150 BP, 57 CC and 95 MF, KEGG pathway analysis yielded 168 signaling pathways. Conclusion Huangqi-Ezhu could treat liver cancer via multi-ingredient, multi-target and multi-pathway.

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备注/Memo

备注/Memo:
国家自然科学基金（81774132）；陕西省中医药管理局科研项目（2021-zz-JC001）；陕西中医药大学消化病肿瘤分子机制及中西医结合防治基础研究创新团队（2019-YS05）。偶勇（1985—），男，硕士学位。研究方向：肿瘤的基础与临床研究。
更新日期/Last Update: 2026-01-15