Literature DB >> 33623529

A Network Pharmacology Approach to Explore the Mechanisms of Artemisiae scopariae Herba for the Treatment of Chronic Hepatitis B.

Asi He1, Wei Wang1, Yang Xia1, Xiaoping Niu1.   

Abstract

BACKGROUND: As a traditional Chinese medicine, Artemisiae scopariae Herba (ASH) is used to treat various liver diseases. The purpose of this study was to explore the mechanisms of ASH for treating chronic hepatitis B (CHB) using a network pharmacological method.
METHODS: Bioactive ingredients and related targets of ASH were obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Gene names of targets were extracted from UniProt database. Differentially expressed genes (DEGs) of CHB were obtained from microarray dataset GSE83148. The intersect genes between DEGs and target genes were annotated using clusterProfiler package. The STRING database was used to obtain a network of protein-protein interactions. Cytoscape 3.7.2 was used to construct the "ingredient-gene-pathway" (IGP) network. Molecular docking studies were performed using Autodock vina.
RESULTS: A total of 13 active components were extracted from TCMSP database. Fifteen intersect genes were obtained between 183 target genes and 403 DEGs of GSE83148. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis results showed that ASH against CHB mainly involved in toll-like receptor signaling pathway, cellular senescence, hepatitis B, and chemokine signaling pathway. We screened one hub compound, five core targets, and four key pathways from constructed networks. The docking results indicated the strong binding activity between quercetin and AKT1.
CONCLUSIONS: This study provides potential molecular mechanisms of ASH against CHB based on exploration of network pharmacology.
Copyright © 2021 Asi He et al.

Entities:  

Year:  2021        PMID: 33623529      PMCID: PMC7875618          DOI: 10.1155/2021/6614039

Source DB:  PubMed          Journal:  Evid Based Complement Alternat Med        ISSN: 1741-427X            Impact factor:   2.629


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