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Evidence-Based Complementary and Alternative Medicine
Volume 2014 (2014), Article ID 495840, 12 pages
Research Article

A Network Pharmacology Approach to Determine Active Compounds and Action Mechanisms of Ge-Gen-Qin-Lian Decoction for Treatment of Type 2 Diabetes

1MOE Key Laboratory of Bioinformatics, Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China
2Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
3Tianjin International Joint Academy of Biotechnology & Medicine, Tianjin 300457, China
4Wuxi Medical School, Jiangnan University, Wuxi 214122, China

Received 23 October 2013; Accepted 11 December 2013; Published 16 January 2014

Academic Editor: Aiping Lu

Copyright © 2014 Huiying Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.