A network pharmacology approach to determine active compounds and action mechanisms of ge-gen-qin-lian decoction for treatment of type 2 diabetes.
A network pharmacology approach to determine active compounds and action mechanisms of ge-gen-qin-lian decoction for treatment of type 2 diabetes.
复制标题
网络药理学方法确定葛根芩连汤治疗2型糖尿病的活性成分和作用机制。
DOI:
10.1155/2014/495840
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发表时间:
2014
期刊:
影响因子:
--
通讯作者:
Tong X
中科院分区:
文献类型:
--
作者:
Li H;Zhao L;Zhang B;Jiang Y;Wang X;Guo Y;Liu H;Li S;Tong X
Traditional Chinese medicine (TCM) herbal formulae can be valuable therapeutic strategies and drug discovery resources. However, the active ingredients and action mechanisms of most TCM formulae remain unclear. Therefore, the identification of potent ingredients and their actions is a major challenge in TCM research. In this study, we used a network pharmacology approach we previously developed to help determine the potential antidiabetic ingredients from the traditional Ge-Gen-Qin-Lian decoction (GGQLD) formula. We predicted the target profiles of all available GGQLD ingredients to infer the active ingredients by clustering the target profile of ingredients with FDA-approved antidiabetic drugs. We also applied network target analysis to evaluate the links between herbal ingredients and pharmacological actions to help explain the action mechanisms of GGQLD. According to the predicted results, we confirmed that a novel antidiabetic ingredient from Puerariae Lobatae radix (Ge-Gen), 4-Hydroxymephenytoin, increased the insulin secretion in RIN-5F cells and improved insulin resistance in 3T3-L1 adipocytes. The network pharmacology strategy used here provided a powerful means for identifying bioactive ingredients and mechanisms of action for TCM herbal formulae, including Ge-Gen-Qin-Lian decoction.
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影响因子:
7.2
作者:
Li, Huan-Ting;Wu, Xiao-Dong;Wang, Jiping
通讯作者:
Wang, Jiping
影响因子:
2.3
作者:
Li, S.;Zhang, Z. Q.;Wang, Y. Y.
通讯作者:
Wang, Y. Y.
影响因子:
4.6
作者:
Li R;Ma T;Gu J;Liang X;Li S
通讯作者:
Li S
影响因子:
64.8
作者:
Jeong, H;Mason, SP;Oltvai, ZN
通讯作者:
Oltvai, ZN
DOI:
10.1073/pnas.1301814110
发表时间:
2013-03-12
影响因子:
11.1
作者:
Bai, Fang;Xu, Yechun;Jiang, Hualiang
通讯作者:
Jiang, Hualiang