AUTHOR=Wang Ning , Du Ninglin , Peng Yonghong , Yang Kuo , Shu Zixin , Chang Kai , Wu Di , Yu Jian , Jia Caiyan , Zhou Yana , Li Xiaodong , Liu Baoyan , Gao Zhuye , Zhang Runshun , Zhou Xuezhong 

TITLE=Network Patterns of Herbal Combinations in Traditional Chinese Clinical Prescriptions

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 11 - 2020

YEAR=2021

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2020.590824

DOI=10.3389/fphar.2020.590824

ISSN=1663-9812

ABSTRACT=As a well-established multi-drug combinations schema, traditional Chinese medicine (herb prescription) has been used for thousands of years in real-world clinical settings. This paper uses complex network approach to investigate the regularities underlying multi-drug combinations in herb prescriptions. Using five collected large-scale real-world clinical herb prescription data sets, we construct five weighted herb combination networks with herb as nodes and herb combinational use in herb prescription as links. We found that weight distribution of herb combinations displays a clear power law, which means that most herb pairs were used in low frequency and some herb pairs were used in very high frequency. Furthermore, we found that it displays clear linear negative correlation between the clustering coefficients and degree of nodes. This indicates that hierarchical properties exist in the herb combination networks. Finally, we evaluate the herb prescriptions using a network-based method at the genetic level, and further explore the relationship between the distribution of herb compatibility and prescriptions evaluation. We found that the more hierarchical prescription, the better the corresponding effect. The results also reflected a well-recognized principle called ‘Jun-Chen-Zhuo-Shi’ in TCM theories. This would also give references for multi-drug combinations development in the field of network pharmacology and also provide guideline for the clinical using of combination therapy for chronic diseases.