Exploration of the Mechanism of Gegen Qinlian Decoction(葛根芩连汤)in Treating Non-alcoholic Fatty Liver Disease Based on Network Pharmacology and Bioinformatics
TANG Gaojun
HU Jie
ZHANG Baofang
Abstract:Objective To explore the mechanism of Gegen Qinlian Decoction(葛根芩连汤)in treating non-alcoholic fatty liver disease(NAFLD)based on network pharmacology and bioinformatics.Methods We downloaded the microarray datasets of GSE89632 and GSE63067 for NAFLD from the GEO database.After data cleaning,we identified differentially expressed genes(DEGs)between healthy individuals and NASH patient samples.Secondly,we downloaded the phenotype genes encoded by NAFLD proteins from the GeneCards database.Using the TCMSP database and relevant literature to screen the main active ingredients and targets of Gegen Qinlian Decoction(葛根芩连汤),matching the target genes corresponding to the targets through the Uniprot protein platform,and then crossing the database dataset and differentially expressed genes on GeneCards with the effective active ingredient targets of Gegen Qinlian Decoction(葛根芩连汤),drawing a Venn diagram and uploading it to the STRING platform for protein protein interaction analysis(PPI).Core genes were mined using different algorithms of Cytoscape,and a core gene protein interaction network and a"Gegen Qinlian Decoction(葛根芩连汤)active ingredient intersection target gene"network were constructed using Cytoscape 3.9.1 software.And perform immune infiltration,immune cell differential analysis,and core gene immune cell differential analysis on intersecting target genes.Perform gene(GO)functional enrichment and(KEGG)pathway enrichment analysis on the target using R software.And predict upstream miRNAs that regulate core genes through the Targeted Scan database,use AutoDock software for molecular docking of small molecule drug ligands with miRNA receptors,and use Pymol for visualization processing.Results 8467 differentially expressed genes were screened from databases such as GEO,146 active ingredients of Gegen Qinlian Decoction(葛根芩连汤)were identified,47 target genes of drug active ingredients intersected with differentially expressed genes in the database,10 core genes,and 10 genes including chemokinase-2(CCL2),interleukin-6(IL-6),heme oxygenase 1(HMOX1),tumor necrosis factor(TNF)were identified as promising diagnostic biomarkers for NAFLD.GO enrichment analysis involves responses to oxidative stress,lipid metabolism,ubiquitin ligase binding,cell necrosis and apoptosis,miRNA transcriptional regulation,etc.KEGG enrichment analysis is used in the PI3K-AKT signaling pathway,non-alcoholic fatty liver disease,NF-κB pathway,and P53 signaling pathway.The intersection gene immune infiltration analysis of drugs and disease targets shows that activated dendritic cells,NK-T cells,NK cells,Tfh cells,Th2,CD8+T cells are the main immune cells infiltrating NAFLD.Differential analysis of immune cells and immune correlation analysis of core genes show that Tfh cells,dendritic cells,Th2,and other core genes are highly correlated with AKT1,STAT3,and other core genes.The molecular docking method was used to verify the strong binding ability of eight active ingredients,including baicalein,kaempferol,and quercetin,to miRNA molecules that regulate core genes.Conclusion This study identified 10 core genes and miRNAs as potential biomarkers for diagnosing NAFLD.Through molecular docking verification,it is suggested that small drug molecules have strong binding ability with miRNA,indicating that miRNA may be a potential regulatory pathway affecting the development of NAFLD.The effective active ingredients of Gegen Qinlian Decoction(葛根芩连汤)provide new clues for the molecular mechanism of treating NAFLD by regulating miRNA and affecting the transcription of core targets.Meanwhile,immune cells such as Tfh,dendritic cells,and Th2 may synergistically affect the progression of NAFLD disease with core genes.
Keywords:bioinformatics analysisnetwork pharmacologyGegen Qinlian Decoction(葛根芩连汤)molecular dockingnon-alcoholic fatty liver disease
Publication Date:2024-11-20
Online Publishing Date:2026-07-17(First online date of this platform, not the publication date of the document)
Pages:14( 26-39 )
