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Chinese Journal of Clinical Pharmacology and Therapeutics ›› 2019, Vol. 24 ›› Issue (10): 1107-1119.doi: 10.12092/j.issn.1009-2501.2019.10.005

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Study on the anti-hyperlipidemia mechanisms and signaling pathways of traditional Chinese medicine Polygonum cuspidatum based on network pharmacology

ZHENG Li, MO Juanfen, WU Jiayuan, GUO Li, BAO Yi   

  1. Key Laboratory, the Second Hospital of Jiaxing, Jiaxing 314000, Zhejiang, China
  • Received:2019-07-18 Revised:2019-08-20 Online:2019-10-26 Published:2019-10-28

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Abstract:

AIM: To analyze the anti-hyperlipidemia effects and signaling pathways of traditional Chinese medicine Polygonum cuspidatum based on network pharmacology and bioinformatics methods. METHODS: The main active ingredients were screened from Polygonum cuspidatum using TCMSP database, and the targets were predicted by Drug-CPI server with reverse pharmacophore matching method. Meanwhile, target databases such as OMIM, TTD and Genecards disease were used to obtain the disease targets of hyperlipidemia, and the intersections of active ingredient targets and disease targets were obtained for further analysis. Cytoscape 3.7.1 software was used to construct the visualization network of "drug-active ingredient-target-disease" of Polygonum cuspidatum.The protein interaction network of the intersecting targets was analyzed by STRING online platform, and the GO function and KEGG pathway enrichment analysis were performed. Furthermore, according to the results of KEGG pathway analysis, the binding energy and and binding mechanism between the active compounds and the key target protein of insulin-resistant pathway and PPAR signaling pathway, namely TNFRSF1A and PPARG were analyzed by using molecular docking software Autodock 4.2.6. RESULTS:Twelve main active ingredients were obtained from Polygonum cuspidatum by TCMSP database, and 288 targets were predicted by Drug-CPI server, meanwhile 571 hyperlipidemia-related disease targets were obtained. Finally, 48 intersections of active ingredient targets and disease targets were obtained. The network of "drug-active ingredient-target-disease" of Polygonum cuspidatum showed that the average degree of compounds in the network was 16.67, and 8 of 12 compounds could interact with 15 or more disease targets. Through the analysis of GO function and KEGG pathway enrichment, the 48 intersecting targets were mainly involved in regulating insulin resistance, PPAR signaling pathway, non-alcoholic fatty liver disease (NAFLD), HIF-1 signaling pathway and Regulation of lipolysis in adipocytes. Molecular docking results showed that all four active components could be spontaneously bind with TNFRSF1A, and rhein had the lowest binding energy with TNFRSF1A, which was -10.08 kcal/mol. Among the seven active components of Polygonum cuspidatum, physovenine has the lowest binding energy with PPARG, which was -13.45 kcal/mol. The binding mode was mainly based on hydrogen bonding, electrostatic force and hydrophobic interaction. CONCLUSION: The active ingredients of Polygonum cuspidatum may regulate lipid metabolism by regulating insulin resistance, PPAR signaling pathway and lipid decomposition, thus realizing the anti-hyperlipidemia effects.

Key words: hyperlipidemia, Polygonum cuspidatum, target prediction, PPAR signaling pathway, insulin resistance

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