基于网络药理学探讨治疗乳难中药共同代谢通路  

Exploring the Co-Metabolism Pathway of Traditional Chinese Medicinesin the Treatment of Lactation Disorder Based on Network Pharmacology

作　　者：沈冰芳 方聪 徐小妹 张亚敏 卢雪花 李丽莎 徐榕青 林文津[1,2] SHEN Bing-fang;Fang Cong;ZHANG Ya-min;XU Xiao-mei;LU Xue-hua;LI Li-sha;XU Rong-qing;LIN Wen-jin(College of Pharmacy,Fujian University of Traditional Chinese Medicine,Fuzhou 350001,China;Fujian Key Laboratory of Medical Analysis,Fujian Academy of Medical Sciences,Fuzhou 350001,China)

机构地区：[1]福建中医药大学药学院,福州350001 [2]福建省医学科学研究院,福建省医学测试重点实验室,福州350001

出　　处：《中国兽药杂志》2023年第7期33-41,共9页Chinese Journal of Veterinary Drug

基　　金：福建省属公益科研院所基本专项(2021R1012001);福建省中医药科研项目(2021ZYYJ71)。

摘　　要：基于网络药理学的方法探讨乳难中药共同代谢通路。遴选2020年版《中国药典》中具有下乳或通乳作用的中药材,应用中药系统药理学分析平台(TCMSP)和中国知网筛选中药材的全部活性成分,并使用TCMSP和Swiss Target Prediction分析平台查询相关靶点。借助UniPort数据库进行基因标准化查询。应用GeneCards数据库和OMIM数据库筛选乳难疾病的靶点;通过在线Venny获得药物疾病的共同靶点。将获得的结果导入Cytoscape软件中进行可视化分析,构建PPI网络,筛选核心靶点。采用Metascape数据库对核心靶点进行GO分析和KEGG相关通路富集。共获得有效活性成分58种,潜在靶点336个,疾病靶点2175个,得到共同靶点158个。GO分析得到生物过程947个,细胞组分29个,分子功能54个,KEGG得到IL-17信号通路、肿瘤坏死因子信号通路等119条通路。利用网络药理学分析平台可对治疗乳难中药的有效成分靶点、乳难疾病靶点以及相关信号通路进行预测,为进一步研究探讨乳难中药共同代谢通路提供了重要依据。To explore the co-metabolism pathway of traditional Chinese medicines in lactation disorder based on network pharmacology.Select the Chinese herbal medicines with milk-reducing or milk-clearing effects in the 2020 edition of the Chinese Pharmacopoeia,all active components of Chinese herbal medicines were screened by TCMSP and CNKI,and related targets were queried using TCMSP and Swiss Target Prediction.Gene normalization query with the help of UniPort database.The GeneCards database and OMIM database were used to screen the targets of breast dysplasia;the common targets of drug diseases were obtained through the online Venny.The obtained results were imported into Cytoscape software for visual analysis,PPI network was constructed,and core targets were screened.The Metascape database was used for GO analysis and KEGG-related pathway enrichment for core targets.Results:A total of 58 active ingredients were obtained,336 potential targets,2175 disease targets,and 158 common targets.GO analysis obtained 947 biological processes,29 cellular components,54 molecular functions,KEGG obtained 119 pathways including IL-17 signaling pathway、TNF signaling pathway.Conclusion:The network pharmacology analysis platform can be used to predict the active ingredient targets,disease targets and pathways of traditional Chinese medicines for lactation disorder which provides an important basis for further research to explore the common metabolic pathways of traditional Chinese medicines for lactation disorder.

关 键 词：网络药理学 中药 乳难 靶点 代谢通路 

分 类 号：S859.79[农业科学—临床兽医学]