基于网络药理学的枸杞子药理作用及其机制研究

Pharmacological Action and Mechanism of Wolfberry Based on Network Pharmacology

目的:采用网络药理学方法对枸杞子成分、靶点、通路、对应疾病进行系统研究。方法:借助TCMSP、GeneCards、UniProt数据库收集枸杞子成分、靶点、对应疾病,通过STRING数据库进行蛋白互作网络分析,并利用DAVID、omicshare平台进行KEGG富集和通路可视化,最后使用Cytoscape软件构建成分、靶点、通路、疾病之间的网络。结果:通过TCMSP、GeneCards、UniProt数据库共收集到枸杞子活性成分45个,靶点203个,疾病24个,疾病主要涉及癌症、高血压、阿尔兹海默症等。使用Cytoscape软件构建成分-靶点网络,筛选主要成分及其靶点。通过DAVID平台,对枸杞子靶点进行KEGG富集分析,筛选到P<0.05的通路119条,通路按P值由小到大排列,对前30条通路可视化,通路主要涉及TNF、HIF-1、p53、PI3K-Akt、Calcium、Toll-like receptor、Thyroid hormone、FoxO、NOD-like receptor等信号通路,以及癌症、乙肝、利什曼病、白血病等疾病通路。结论:该研究通过构建枸杞子成分-靶点-通路-疾病网络,为枸杞子在临床应用及机制研究方面提供了方向和思路。

Objective:To systematically study the components,targets,pathways and corresponding diseases of wolfberry by network pharmacology.Methods:TCMPS、GeneCards and UniProt databases were used to collect wolfberry components、targets、diseases,protein interaction network analysis through STRING database,KEGG enrichment and pathway visualization using DAVID and omicshare platforms,and finally using Cytoscape software to construct a network of targets、pathways and diseases.Results:A total of 45 active components of wolfberry,203 targets,and 24 diseases were collected by TCMSP、GeneCards and UniProt databases.The diseases mainly involved cancer,hypertension,and Alzheimer′s disease.The component-target network was constructed using Cytoscape software to screen the major components and their targets.Through the DAVID platform,KEGG enrichment analysis was performed on the target of wolfberry,and 119 channels of P<0.05 were screened.The pathways were arranged from small to large by P values,and the first 30 pathways were visualized.The pathway mainly involved TNF、HIF-1、p53、PI3K-Akt、Calcium、Toll-like receptor、Thyroid hormone、FoxO、NOD-like receptor and other signaling pathways,as well as cancer、hepatitis B、leishmaniasis、leukemia and other disease pathways.Conclusion:This study provides a direction and ideas for the clinical application and mechanistic research of wolfberry by constructing a wolfberry component-target-path-disease network.