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基于网络药理学探讨消癥丸治疗子宫肌瘤的活性成分及作用靶点

Network pharmacology evaluation of the active ingredients and potential targets of XiaoLuoWan for application to uterine fibroids.

机构信息

Gynecological Department of Traditional Chinese Medicine, China-Japan Friendship Hospital, Beijing 100029, P.R. China.

出版信息

Biosci Rep. 2020 Dec 23;40(12). doi: 10.1042/BSR20202342.

Abstract

XiaoLuoWan (XLW) is a classical formula in traditional Chinese medicine (TCM) that has satisfactory therapeutic effects for uterine fibroids (UFs). However, its underlying mechanisms remain unclear. To elucidate the pharmacological actions of XLW in treating UFs, an ingredient-target-disease framework was proposed based on network pharmacology strategies. The active ingredients in XLW and their putative targets were obtained from the TCM systems pharmacology database and analysis platform (TCMSP) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM) platforms. The known therapeutic targets of UFs were acquired from the DigSee and DrugBank databases. Then, the links between putative XLW targets and therapeutic UF targets were identified to establish interaction networks by Cytoscape. Finally, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of overlapping gene targets were performed in the STRING database and visualized in R software. In total, 9 active compounds were obtained from 74 ingredients, with 71 curative targets predicted in XLW. Moreover, 321 known therapeutic targets were closely related to UFs, with 29 targets overlapping with XLW and considered interacting genes. Pathway enrichment revealed that the calcium signaling pathway was significantly enriched and the mitogen-activated protein kinase (MAPK) signaling pathway, cAMP signaling pathway, cancer and vascular smooth muscle contraction pathways, cGMP-PKG signaling pathway, and AGE-RAGE signaling pathway were closely associated with XLW intervention for UFs. In conclusion, the network pharmacology detection identified 9 available chemicals as the active ingredients in XLW that may relieve UFs by regulating 29 target genes involved in the calcium signaling pathway, MAPK pathway and cAMP pathway. Network pharmacology analyses may provide more convincing evidence for the investigation of classical TCM prescriptions, such as XLW.

摘要

消癥丸(XLW)是一种经典的中药方剂,对子宫肌瘤(UFs)有满意的疗效。然而,其作用机制尚不清楚。为阐明 XLW 治疗 UFs 的药理作用,采用网络药理学策略提出了成分-靶标-疾病框架。从中药系统药理学数据库和分析平台(TCMSP)和生物信息学分析工具用于中药分子机制(BATMAN-TCM)平台获得 XLW 的活性成分及其假定靶点。从 DigSee 和 DrugBank 数据库中获得 UFs 的已知治疗靶点。然后,通过 Cytoscape 识别假定的 XLW 靶点和治疗 UF 靶点之间的联系,建立相互作用网络。最后,在 STRING 数据库中对重叠基因靶点进行基因本体论(GO)富集和京都基因与基因组百科全书(KEGG)通路分析,并在 R 软件中可视化。总共从 74 种成分中获得 9 种活性化合物,预测 XLW 中有 71 个治疗靶点。此外,321 个已知的治疗靶点与 UFs 密切相关,有 29 个靶点与 XLW 重叠,被认为是相互作用基因。通路富集分析表明,钙信号通路显著富集,丝裂原激活蛋白激酶(MAPK)信号通路、cAMP 信号通路、癌症和血管平滑肌收缩通路、cGMP-PKG 信号通路和 AGE-RAGE 信号通路与 XLW 干预 UFs 密切相关。总之,网络药理学检测鉴定出 9 种有效化学物质作为 XLW 的活性成分,可能通过调节钙信号通路、MAPK 通路和 cAMP 通路中的 29 个靶基因缓解 UFs。网络药理学分析可为研究经典中药方剂,如 XLW,提供更有说服力的证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dabe/7724689/2716ad281869/bsr-40-bsr20202342-g1.jpg

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