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结合化学分析和网络分析研究中药复方的药理学。

Combining Chemical Profiling and Network Analysis to Investigate the Pharmacology of Complex Prescriptions in Traditional Chinese Medicine.

机构信息

College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, PR China.

Tianjin Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, PR China.

出版信息

Sci Rep. 2017 Jan 13;7:40529. doi: 10.1038/srep40529.

DOI:10.1038/srep40529
PMID:28084407
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5233960/
Abstract

We present a paradigm, combining chemical profiling, absorbed components detection in plasma and network analysis, for investigating the pharmacology of combination drugs and complex formulae. On the one hand, the composition of the formula is investigated comprehensively via mass spectrometry analysis, followed by pharmacological studies of the fractions as well as the plasma concentration testing for the ingredients. On the other hand, both the candidate target proteins and the effective ingredients of the formula are predicted via analyzing the corresponding networks. The most probable active compounds can then be identified by combining the experimental results with the network analysis. In order to illustrate the performance of the paradigm, we apply it to the Danggui-Jianzhong formula (DJF) from traditional Chinese medicine (TCM) and predict 4 probably active ingredients, 3 of which are verified experimentally to display anti-platelet activity, i.e., (Z)-Ligustilide, Licochalcone A and Pentagalloylglucose. Moreover, the 3-compound formulae composed of these 3 chemicals show better anti-platelet activity than DJF. In addition, the paradigm predicts the association between these 3 compounds and COX-1, and our experimental validation further shows that such association comes from the inhibitory effects of the compounds on the activity of COX-1.

摘要

我们提出了一种范式，将化学分析、血浆中吸收成分的检测和网络分析结合起来，用于研究组合药物和复杂配方的药理学。一方面，通过质谱分析全面研究配方的组成，然后对各馏分进行药理学研究以及对成分的血浆浓度进行检测。另一方面，通过分析相应的网络来预测候选靶蛋白和配方的有效成分。然后，通过将实验结果与网络分析相结合，确定最可能的活性化合物。为了说明该范式的性能，我们将其应用于来自中药（TCM）的当归建中配方（DJF），并预测了 4 种可能的活性成分，其中 3 种经实验验证具有抗血小板活性，即（Z）-藁本内酯、甘草查尔酮 A 和五没食子酰葡萄糖。此外，由这 3 种化学物质组成的 3 种化合物配方显示出比 DJF 更好的抗血小板活性。此外，该范式预测了这 3 种化合物与 COX-1 之间的关联，我们的实验验证进一步表明，这种关联来自于化合物对 COX-1 活性的抑制作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/dca24f489a84/srep40529-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/19041cf6ccb4/srep40529-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/d6adbea4d473/srep40529-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/b44bd0ec6073/srep40529-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/4c49e64f4eec/srep40529-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/0a6a66c82d12/srep40529-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/3b4eef07ed8f/srep40529-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/dca24f489a84/srep40529-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/19041cf6ccb4/srep40529-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/d6adbea4d473/srep40529-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/b44bd0ec6073/srep40529-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/4c49e64f4eec/srep40529-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/0a6a66c82d12/srep40529-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/3b4eef07ed8f/srep40529-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5233960/dca24f489a84/srep40529-f7.jpg

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