Scinovex
review Open AccessTop 1% cited

Network Pharmacology Databases for Traditional Chinese Medicine: Review and Assessment

Frontiers in Pharmacology · 2019 · Vol. 10 · pp. 123–123
Runzhi ZhangXue ZhuHong BaiKang Ning

Abstract

The research field of systems biology has greatly advanced and, as a result, the concept of network pharmacology has been developed. This advancement, in turn, has shifted the paradigm from a "one-target, one-drug" mode to a "network-target, multiple-component-therapeutics" mode. Network pharmacology is more effective for establishing a "compound-protein/gene-disease" network and revealing the regulation principles of small molecules in a high-throughput manner. This approach makes it very powerful for the analysis of drug combinations, especially Traditional Chinese Medicine (TCM) preparations. In this work, we first summarized the databases and tools currently used for TCM research. Second, we focused on several representative applications of network pharmacology for TCM research, including studies on TCM compatibility, TCM target prediction, and TCM network toxicology research. Third, we compared the general statistics of several current TCM databases and evaluated and compared the search results of these databases based on 10 famous herbs. In summary, network pharmacology is a rational approach for TCM studies, and with the development of TCM research, powerful and comprehensive TCM databases have emerged but need further improvements. Additionally, given that several diseases could be treated by TCMs, with the mediation of gut microbiota, future studies should focus on both the microbiome and TCMs to better understand and treat microbiome-related diseases.

Pharmacological Effects of Natural CompoundsChromatography in Natural ProductsMetabolomics and Mass Spectrometry StudiesSystems pharmacologyTraditional Chinese medicineComputer scienceComputational biologyMedicinePharmacologyDrugBiologyAlternative medicine
Citations
1,202
FWCI
116.73
field-weighted impact
References
122
Percentile
100%
vs. same field & year
Citations per year
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.