Research into the mechanism of intervention of Wenjing decoction in endometriosis based on network pharmacology and molecular docking technology

Abstract

Background: Endometriosis (EMs) is a frequent disease in women and is the principal cause of infertility and dysmenorrhea. Due to its high recurrence rate and serious complications, more research on EMs is needed. We used network pharmacology and molecular docking technology to predict the key active components, targets, and signaling pathways of Wen Jing decoction (WJD) in the treatment of EMs.

Methods: The components and targets of WJD were collected and identified using the Traditional Chinese Medicine Systems Pharmacology Database and BATMAN-TCM. The EMs targets were obtained from GeneCards, OMIM, TTD, Kyoto encyclopedia of genes and genomes (KEGG) and GAD Databases; the Venny diagram was used to analyze the overlap between the targets of WJD and EMs; use Cytoscape 3.8.2 software to build a drug active ingredient-target protein interaction network; after downloading the data from the String online database, Cytoscape 3.8.2 software was used to draw the intersection target protein-protein interaction network diagram. Finally, microbiotic information mapping was used to analyze gene ontology function enrichment and KEGG pathway enrichment. Molecular docking was used to predict the binding affinity of the components of WJD to the targets of EMs.

Results: Seventy-eight active ingredients of WJD were screened, corresponding to 108 targets, 2626 EMs-related targets and 124 intersection targets. The results of gene ontology functional enrichment analysis showed that WJD could affect 709 biological processes, 131 molecular functions and 54 cell composition. The enrichment analysis of KEGG pathway yielded 185 pathways. The treatment of EMs by WJD has the characteristics of multiple targets and multiple pathways. Molecular docking with the AutoDock Vina platform found that 5 active ingredients of WJD were successfully docked with 6 common targets.

Conclusion: Based on network pharmacology and molecular docking, WJD was found to act on EMs through multi-targets and related signaling pathways.

Figure 1.

The herbs-compounds-genes multinetwork.

Figure 2.

Overlapping target genes between drug and EMs.

Figure 3.

Intersectional target interaction network. The more a target is connected to other targets, the more important the target is.

Figure 4.

Core target screening. Note: Picture above is the core target, where the larger the node, the higher the degree value.

Figure 5.

Top 30 targets of WJD in the treatment of EMs.

Figure 6.

GO analysis results. Note: Left side of the picture above demonstrates the top 10 significantly enriched BP, CC, and MF categories, while below the picture shows the number of enriched genes for these terms (P < .05). GO = gene ontology, BP = biological process, CC = cellular component, MF = molecular function.

Figure 7.

Bubble map of 18 KEGG pathway. Note: The y-axis demonstrates the top 18 significantly enriched KEGG pathways, while the x-axis shows the number of enriched genes for these terms (P < .05), the colors and the sizes indicate different P-value ranges; the redder and bigger it is, the more significantly enriched it is. KEGG = Kyoto Encyclopedia of Genes and Genomes.

Figure 8.

Disease-drug-active ingredient-target-signaling pathway interaction network, resulting in a network containing 277 nodes and 760 edges. Note: Light red represents the signaling pathway, orange represents the target, and green represents the drug component.

Figure 9.

According to the size of the binding energy, 30 molecular docking model results are shown by heat maps.

Figure 10.

Visualization result of molecular docking AKT1(PDB:3MVH)-paeoniflorin.

Figure 11.

Visualization result of molecular docking AKTI(PDB:3MVH)-kaempferol.

Figure 12.

Visualization result of molecular docking AKTI(PDB:3MVH)-quercetin.

Figure 13.

Visualization result of molecular docking EGFR(PDB:3GKW)-quercetin.