基于网络药理学的木通治疗泌尿系统疾病的分子机制研究

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Abstract Objective To explore the active components and molecular mechanism of Akebia Decne in the treatment of urinary system diseases from the perspective of network pharmacology.Methods Active ingredients and targets were obtained through Traditional Chinese Medicines Systems Pharmacology(TCMSP),urinary disease-related targets were obtained through OMIM and Genecard databases,and the active ingredients-targets network was bulit by using cytoscape_3.7.2.Through the STRING database,the protein-protein interaction network was constructed,and the core targets were obtained by network topology analysis with Bisogenet plug-in of Cytoscape.Then Autodock vina was used to verify the molecular docking between the active ingredients and the targets.Finally,core targets data were imported into Metascape to obtain GO biological process enrichment analysis and KEGG pathway enrichment analysis.Results The active ingredient-targets network of Akebia Decne involved 8 active ingredients and 51 targets.The results of docking showed that the active ingredients had good binding ability with the corresponding targets.Twenty GO biological process analysis and 20 KEGG pathways were determined.GO biological process analysis mainly involved apoptotic signaling pathway,cell division,cellular response to nitrogen compound,cellular response to oxidative stress and regulation of cellular response to stress.KEGG pathway analysis results showed that the regulation of the urinary system mainly involved MAPK pathway,mitochondrial autophagy,p53 signaling pathway and bacterial infection.Conclusion The treatment of urinary system diseases by Akebia Decne is the result of the interaction of multiple compounds,multiple targets and multiple pathways,which provides a theoretical basis for the further experimental verification.

Key words： Akebia Decne Network pharmacology Urinary system diseases Molecular docking Mechanism of action

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	WU Geng-fan

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WU Geng-fan. Study on molecular mechanisms of Akebia Decne in treatment of urinary system diseases based on network pharmacology[J]. 中国当代医药, 2021, 28(13): 17-24.

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http://dangdaiyiyao.com/EN/ OR http://dangdaiyiyao.com/EN/Y2021/V28/I13/17

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