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Archive > Volume 11 Issue 4 > 2019,11(4):349-356. DOI:10.1016/j.chmed.2019.08.003 Prev Next

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Prediction of quality markers of traditional Chinese medicines based on network pharmacology

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    摘要:


    Abstract:
    Network pharmacology is a powerful tool to reflect the pharmacologically active effects, mechanism of action and toxic activity of traditional Chinese medicines (TCMs). The ingredients of TCMs, associated with quality control of TCM products, are those fundamental chemicals that exhibit biological activities. A great amount of effort has been made by scientists in that field in order to improve the quality of TCMs, though the approaches to determine their quality and the TCM theory and compatibility rules remain ambiguous. Now some methods and technologies must be applied to predict and explore the quality marker (Q-marker) for quality control, as well as to clarify the factors affecting the quality of TCM, which may give new insight into rational ground of establishment of appropriate quality control and assessment system. In this review paper, authors focus on the prediction of quality markers of TCMs by network pharmacology based on three aspects: (1) from network medicine to network pharmacology, (2) complex network system of traditional Chinese medicine, and (3) predicting TCM quality markers based on network pharmacology. Authors proposed the research pattern on network pharmacology based on biological and medical networks, and further TCM network pharmacology based on substantial basis of TCM formulae, and the idea of “effect-ingredient-target-fingerprint” to predict and recognize the TCM Q-marker was the ultimate goal. In addition, authors yet noted how to make full use of the advantages of network toxicology to provide new ideas for the toxicity study of complex TCM systems and the prediction of TCM toxicity markers.

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    Project Supported:
    National Nature Science Foundation for Key Projects (No. 81430096), National New Drug Innovation (No. 2017ZX09301062.) and Tianjin Science and Technology Plan Project (No. 19YFSLQY00110)

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