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

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.

Figure 1

Workflow chart of Artemisiae scopariae Herba in the treatment of chronic hepatitis B based on network pharmacology.

Figure 2

Differentially expressed genes (DEGs) in volcano plot. Green and red dots indicate downregulated and upregulated genes, respectively, on the basis of |log2FoldChange| > 1 and adjusted p value <0.05.

Figure 3

Venn diagram of drug genes (blue) and differentially expressed genes (red).

Figure 4

Functional annotation of 15 intersect genes by (a) biological process and (b) KEGG pathway.

Figure 5

Ingredient-gene-pathway network. The purple triangles, yellow ellipses, and green octagons represent pathways, intersect target genes, and effective ingredients of ASH, respectively. The larger the shape of the graph, the greater the degree value of the node, and the greater the role in the network.

Figure 6

Pearson's correlation analysis of the hub genes in GSE83148. Yellow indicates significant positive correlation.

Figure 7

Target protein interaction network and hub targets analysis. The nodes and edges indicate proteins and protein-protein associations, respectively. Red nodes represent core proteins. The larger the round shape, the greater the degree value of the node.

Figure 8

Molecular docking diagram. Molecular models of the binding of AKT1, CCL2, CXCL8, and FOS with quercetin, the results shown as 3D diagrams. (a) Quercetin-AKT1 (AV = −9.3 kcal/mol); (b) quercetin-CCL2 (AV = −5.8 kcal/mol); (c) quercetin-CXCL8 (AV = −6.6 kcal/mol); (d) quercetin-FOS (AV = −6.1 kcal/mol).