Zeng Liuting, Yang Kailin, Liu Huiping, Zhang Guomin
The Basic Medical Laboratory of Hunan University of Chinese Medicine, Changsha, Hunan 410208, P.R. China.
Exp Ther Med. 2017 Nov;14(5):4697-4710. doi: 10.3892/etm.2017.5170. Epub 2017 Sep 21.
To investigate the pharmacological mechanism of Guizhi Fuling Wan (GFW) in the treatment of uterine fibroids, a network pharmacology approach was used. Information on GFW compounds was collected from traditional Chinese medicine (TCM) databases, and input into PharmMapper to identify the compound targets. Genes associated with uterine fibroids genes were then obtained from the GeneCards and Online Mendelian Inheritance in Man databases. The interaction data of the targets and other human proteins was also collected from the STRING and IntAct databases. The target data were input into the Database for Annotation, Visualization and Integrated Discovery for gene ontology (GO) and pathway enrichment analyses. Networks of the above information were constructed and analyzed using Cytoscape. The following networks were compiled: A compound-compound target network of GFW; a herb-compound target-uterine fibroids target network of GWF; and a compound target-uterine fibroids target-other human proteins protein-protein interaction network, which were subjected to GO and pathway enrichment analyses. According to this approach, a number of novel signaling pathways and biological processes underlying the effects of GFW on uterine fibroids were identified, including the negative regulation of smooth muscle cell proliferation, apoptosis, and the Ras, wingless-type, epidermal growth factor and insulin-like growth factor-1 signaling pathways. This network pharmacology approach may aid the systematical study of herbal formulae and make TCM drug discovery more predictable.
为研究桂枝茯苓丸(GFW)治疗子宫肌瘤的药理机制,采用了网络药理学方法。从中药(TCM)数据库收集GFW化合物信息,并输入到PharmMapper中以识别化合物靶点。然后从GeneCards和《人类孟德尔遗传在线》数据库中获取与子宫肌瘤基因相关的基因。靶点与其他人类蛋白质的相互作用数据也从STRING和IntAct数据库中收集。将靶点数据输入到基因本体论(GO)和通路富集分析的注释、可视化和综合发现数据库(DAVID)中。使用Cytoscape构建并分析上述信息的网络。编制了以下网络:GFW的化合物-化合物靶点网络;GWF的草药-化合物靶点-子宫肌瘤靶点网络;以及化合物靶点-子宫肌瘤靶点-其他人类蛋白质的蛋白质-蛋白质相互作用网络,并对其进行了GO和通路富集分析。根据该方法,确定了一些GFW对子宫肌瘤作用的新信号通路和生物学过程,包括平滑肌细胞增殖的负调控、凋亡以及Ras、无翅型、表皮生长因子和胰岛素样生长因子-1信号通路。这种网络药理学方法可能有助于对中药方剂进行系统研究,并使中药药物发现更具可预测性。