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Emerging network pharmacology (NP) combines phytochemical information with bioinformatics tools allowing herbal formulae to be illustrated holistically in the context of phytochemical basis and therapeutic mechanisms. This study attempted to explore the holistic molecular evidence of herbal formula Si-Wu decoction (SWD) by using the method of NP. Databases of traditional medicines combined with PubChem, SciFinder, SEA, STRING, and KEGG were employed to gather information for establishing the "compound similarity" (CS) network and the "target-(pathway)-target" (TPT) network. Gephi software was applied to visualise the networks, with further module-based and node-based network topological analysis. Moreover, the approved drugs and shortest path analysis were used to validate the TPT network. The CS network presented the phytochemical profile of SWD, including the major compound groups of iridoid glycosides, glycosides, phthalide lactones, phenylpropanoids, and monoterpenoids. Furthermore, the topological analysis of TPT network depicted the holistic property of SWD in interpretable neuroendocrine immunomodulation (NIM) perspective, and the node degree analysis indicated a closer connection of SWD with endocrine or metabolism system. Moreover, by combing the analysis of the CS network and TPT network, potential active ingredients could be primarily identified. The phytochemical profile and molecular target profile, which might pave the way for an understanding of SWD in modern science and provide a reference for relevant quality research and evaluation, were demonstrated by network analysis. Moreover, the methods could be further applied to discover the phytochemical or biomolecular evidence with distinct advantages in dealing with the tremendous separated information. © 2020 John Wiley & Sons, Ltd.

Citation

Hua-Li Zuo, Qian-Ru Zhang, Cen Chen, Feng-Qing Yang, Hua Yu, Yuan-Jia Hu. Molecular evidence of herbal formula: a network-based analysis of Si-Wu decoction. Phytochemical analysis : PCA. 2021 Apr;32(2):198-205

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PMID: 32519355

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