Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology-Based Identification

Abstract

Endometriosis is a common benign disease in women of reproductive age. It has been defined as a disorder characterized by inflammation, compromised immunity, hormone dependence, and neuroangiogenesis. Unfortunately, the mechanisms of endometriosis have not yet been fully elucidated, and available treatment methods are currently limited. The discovery of new therapeutic drugs and improvements in existing treatment schemes remain the focus of research initiatives. Chinese medicine can improve the symptoms associated with endometriosis. Many Chinese herbal medicines could exert antiendometriosis effects via comprehensive interactions with multiple targets. However, these interactions have not been defined. This study used association rule mining and systems pharmacology to discover a method by which potential antiendometriosis herbs can be investigated. We analyzed various combinations and mechanisms of action of medicinal herbs to establish molecular networks showing interactions with multiple targets. The results showed that endometriosis treatment in Chinese medicine is mainly based on methods of supplementation with blood-activating herbs and strengthening qi. Furthermore, we used network pharmacology to analyze the main herbs that facilitate the decoding of multiscale mechanisms of the herbal compounds. We found that Chinese medicine could affect the development of endometriosis by regulating inflammation, immunity, angiogenesis, and other clusters of processes identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The antiendometriosis effect of Chinese medicine occurs mainly through nervous system-associated pathways, such as the serotonergic synapse, the neurotrophin signaling pathway, and dopaminergic synapse, among others, to reduce pain. Chinese medicine could also regulate VEGF signaling, toll-like reporter signaling, NF-κB signaling, MAPK signaling, PI3K-Akt signaling, and the HIF-1 signaling pathway, among others. Synergies often exist in herb pairs and herbal prescriptions. In conclusion, we identified some important targets, target pairs, and regulatory networks, using bioinformatics and data mining. The combination of data mining and network pharmacology may offer an efficient method for drug discovery and development from herbal medicines.

Keywords: bioinformatics; data mining; endometriosis; medicinal herb; network analysis; network pharmacology.

Figure 1

Workflow of the systems pharmacology approach. (A) Method (1) Endometriosis-associated genes were integrated from three different sources: the Genecard database, PubMed database, Genbank, and the Online Mendelian Inheritance in Man (OMIM) database. (2) Construction of protein-protein interaction (PPI) topological modules. Gene Ontology (GO) and pathway enrichment functional analyses were conducted for the endometriosis and Chinese medicine targets modules. (3) Disease-related conventional medication targets from the Therapeutic Target Database (TTD) and DrugBank databases, guidelines, and published literature. (4) KEGG and GO analyses of the targets of major compounds. (5) Analysis of the targets of endometriosis and pathways that Chinese herbs could regulate. (B) Workflow of literatures search for data mining.

Figure 2

Data mining of Chinese herbs from literature. (A) Ratio of herbs of different classifications. Traditional Chinese medicine includes tonics, heat-clearing medicines, and blood-activating and stasis-removing medicines. (B–D) Ratios of the taste and action of Chinese herbs. Among the Chinese herbs evaluated, most were used as warm drugs, mainly targeting the liver and spleen. (E, F) Knowledge Graphs of major Chinese herbs. The size of a node represents the frequency of Traditional Chinese medicine in our gynecological dataset of Chinese medicine. The node represents the knowledge element, Chinese medicine. Cosine distance of the knowledge meta-semantic representation vector, a feature of clustering, was evaluated. Based on the association rules, frequent itemsets and recurrent neural networks (RNNs), the knowledge graphs were constructed, which were divided into four clusters and nine clusters, respectively. The knowledge graphs may provide the basis for the discovery of relevant prescriptions. Cluster analysis could also provide a reference for prescription guidelines.

Figure 3

Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis of endometriosis-associated genes. (A) Venn diagram showing analysis of endometriosis genes from different datasets. MMP2, PTEN, LHB, BIRC5, EMX2, ENDO1, KRAS, NR5A1, AHRR, CCL11, MMP14, CCL5, ESR2, ARID1A, and MMP9 were the shared genes from the Genecard, Genbank, and OMIM datasets. (B) GO enrichment of endometriosis-associated genes. (C) KEGG pathway of endometriosis genes. Bubble chart for significantly enriched pathway terms from KEGG analysis. The size of each bubble is reflective of the relative ratio of the number of targets hitting each pathway over the total number of targets. P indicates the statistical significance of the P-values; greater numbers indicate greater significance. (D) Hub genes of endometriosis-associated genes, determined by cytoHubba in Cytoscape 3.7.2. (E) Cluster analysis of endometriosis-associated genes, determined by Molecular Complex Detection (MCODE) in Cytoscape 3.7.2.

Figure 4

Multiregulation effect of all targets in selected Chinese medicines. These traditional Chinese medicines are mainly therapeutic medicines and official prescription medicines, which could regulate multiple pathways involving nerves, inflammation, and immunity. These actions reflect the multitarget regulatory mechanisms of Traditional Chinese medicine. (A) Venn diagram showing the common targets between Chinese herbs and conventional treatment drugs. (B) Gene Ontology (GO) enrichment analysis of Chinese herbs and associated targets. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in annotation. (D) KEGG pathway enrichment of the targets of Chinese herbs. (E) Module analysis of Chinese herbs, determined by Molecular Complex Detection (MCODE) of the Cytoscape software. These targets could be divided into 13 clusters. The MCODE_2 (pathways in cancer and response to reactive oxygen species); MCODE_3 (cytochrome P450 - arranged by substrate type); MCODE_6 (cellular responses to stress), MCODE_7 and MCODE_12 (apoptosis); MCODE_9 (adenylate cyclase-activating G protein-coupled receptor signaling pathway, cAMP-mediated signaling pathway); and MCODE_11 (VEGFR2 mediated cell proliferation, Ras signaling pathway) were all related to endometriosis pathogenesis.

Figure 5

Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses of the targets of Chinese medicine in endometriosis treatment. (A) GO analysis of the targets of endometriosis-associated genes that coincided with those of Chinese herbs. (B) KEGG enrichment of endometriosis-associated genes that coincided with those of Chinese herbs. (C) Pathways and targets network of Chinese medicine in endometriosis treatment. (D) Module analysis of the targets of Chinese medicine in endometriosis treatment, determined by Molecular Complex Detection (MCODE) of the Cytoscape software.

Figure 6

Pathway of multiregulatory effects in Chinese medicine. Target network showing multiregulation in Chinese medicine. The reconstructed Kyoto Encyclopedia of Genes and Genomes (KEGG) map reflects the multipath, multitarget regulatory pathway of Chinese medicine. Target names are shown in rectangles. The pathway network with a blue background is a pathway module that is directly related to endometriosis in Chinese medicine. The green background indicates the network of Chinese medicine that regulates endometriosis-associated pain and estrogen regulatory pathways. The red border indicates the direct target for Chinese medicine treatment in endometriosis. The black border indicates the indirect target. The arrows in the figure indicate the upstream and downstream genes in pathway actions of the targets. Interactions between the pathways were noted. Each pathway target synergistically regulates endometriosis pain, inflammation and immunity, adhesion, invasion, and angiogenesis.

Figure 7

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and sub-network analysis of traditional Chinese medicine for the endometriosis pain module. The pain module in endometriosis showed multiple neurotransmitters, nervous system pathways, and direct involvement in pain regulation. (A) KEGG mapper of the serotonergic synapse. (B) The network of targets network of pain associated pathways. Pathway of multineurotransmitter and inflammation, and immunity regulation network in endometriosis-associated pain. Purple nodes represent pathways, and blue nodes represent targets. (C) The protein-protein interaction (PPI) network of pain associated genes in Chinese medicine treatment. (D) Network of major compounds and targets in endometriosis-associated pain treatment. The middle green node represents pain treatment-related compounds, and the surrounding nodes are composed of different colors, which represent the target points enriched, according to the pathways. And the yellow node represents pathways.

Figure 8

Discovery of potential compounds. (A) Venn diagram of major Chinese herbs associated targets. The venn diagram reflects the similarity of these Chinese medicines in regulating targets. (B) Network analysis to decipher the synergistic mechanisms of the compound-target network. We selected natural compounds that may have therapeutic effects for endometriosis and combined that information with molecular docking results. The compounds were derived from data mining of common Chinese herbs. Relationship between formula targets and drug targets. The network was constructed with compounds sharing the same targets between compounds. The data represents the ratio of formula targets and drug targets in biological processes. Blue nodes represent targets and orange nodes represent compounds. The deeper the color of a node, the more frequently it appears. Deeper colors may be the main targets and compounds. The bigger font size, the greater its degree based on undirected network analyisis. The major compounds were showed in Table 6.

Figure 9

Potential mechanism of action of Chinese herbs/compounds in endometriosis. Based on the results of our network pharmacological analysis, polyphenolic compounds, sesquiterpenes, terpenoids, flavonoids, alkaloids, polysaccharides, and steroid glycosides are commonly used for the treatment of endometriosis. Traditional Chinese medicine for treating endometriosis includes regulating estrogen receptors, regulating nerve-related receptors, regulating inflammatory and immunity, inhibiting invasion, adhesion, and angiogenesis, affecting the kinase signalling pathways. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the treatment of endometriosis with Chinese medicine is regulated by multiple cross-talk pathways. Such treatments could act directly on neurotransmitter-related pathways and the estrogen pathway, which is similar to the action of conventional treatment. Chinese medicine also could regulate adhesion, invasion, and angiogenesis by regulating PI3K-Akt signaling, toll-like receptor signaling, NF-κB signaling, and the MAPK signaling pathway, among others.