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How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

Yuan, Haidan, Ma, Qianqian, Cui, Heying, Liu, Guancheng, Zhao, Xiaoyan, Li, Wei, Piao, Guangchun·2017·Molecules
DOI 10.3390/molecules22071135
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Abstract

Abstract: Many prescriptions of traditional medicines (TMs), whose efficacy has been tested in clinical practice, have great therapeutic value and represent an excellent resource for drug discovery. Research into single compounds of TMs, such as artemisinin from Artemisia annua L., has achieved great success; however, it has become evident that a TM prescription (which frequently contains various herbs or other components) has a synergistic effect in effecting a cure or reducing toxicity. Network pharmacology targets biological networks and analyzes the links among drugs, targets, and diseases in those networks. Comprehensive, systematic research into network pharmacology is consistent with the perspective of holisticity, which is a main characteristic of many TMs. By means of network pharmacology, research has demonstrated that many a TM show a synergistic effect by acting at different levels on multiple targets and pathways. This approach effectively bridges the gap between modern medicine and TM, and it greatly facilitates studies into the synergistic actions of TMs. There are different kinds of synergistic effects with TMs, such as synergy among herbs, effective parts, and pure compounds; however, for various reasons, new drug discovery should at present focus on synergy among pure compounds.

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Metadata

Authors
Yuan, H., Ma, Q., Cui, H., Liu, G., Zhao, X., Li, W., & Piao, G.
Venue
Molecules
Publisher
MDPI AG
Published
2017-07-07
Volume
22
Issue
7
Pages
1135
ISSN
1420-3049
DOI
10.3390/molecules22071135
Cited by
392
References
1
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
National Natural Science Foundation of China (81560698, 81660614)

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Yuan, H., Ma, Q., Cui, H., Liu, G., Zhao, X., Li, W., & Piao, G. (2017). How Can Synergism of Traditional Medicines Benefit from Network Pharmacology? Molecules. https://doi.org/10.3390/molecules22071135

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