The action mechanism of the Jianpi Huazhuo decoction on treating dyslipidemia based on network pharmacology
Objective:To explore the action mechanism of the Jianpi Huazhuo decoction(健脾化浊汤)on dyslipidemia based on network pharmacology and molecular docking methods.Methods:The active ingredients of the Jianpi Huazhuo decoction were retrieved by TCMSP platform,and the compound ingredient targets were screened out by SwissTargetPrediction,DrugBank,and Batman-TCM.In 8 databases including TTD and 1 comprehensive gene expression databas GEO,the targets of dyslipidemia were obtained from the Affymetrix gene microarray.Cytoscape 3.2.1 was used to draw the active ingredient-therapeutic target network,and the component target-disease target network.STRING database was used to construct a protein interaction network,and R language software was used for GO function enrichment analysis and KEGG pathway enrichment analysis.Finally,iGEMDOCK was used for molecular docking.Results:A total of 70 active ingredients of the Jianpi Huazhuo decoction and 109 therapeutic targets were screened out.The core targets included insulin,AKT1,EGFR,PTGS2,APP,ESR1,etc..Based on KEGG enrichment analysis,it was predicted that the signaling pathways involved in the treatment of dyslipidemia with the Jianpi Huazhuo decoction mainly included PI3K/Akt signaling pathway,PPAR signaling pathway,Rapl signaling pathway,insulin resistance pathway,and HIF1 signaling pathway.The results of molecular docking showed that the main active components of the Jianpi Huazhuo decoction had relatively stable binding activity with the core targets.Conclusion:Based on the research on the active ingredients,key targets and related pathways of the Jianpi Huazhuo decoction in the treatment of dyslipidemia,it is believed that the Jianpi Huazhuo decoction may mainly play a role in regulating blood lipids by regulating insulin secretion,ameliorating insulin resistance,regulating receptors and enzymes related to lipoprotein metabolism,and inhibiting cholesterol absorption,providing ideas for future pharmacology and clinical research.
万方数据
维普
