Method for treating chronic pelvic inflammation by using motherwort herb based on network pharmacology analysis

Abstract

The invention discloses a method for analyzing treatment of chronic pelvic inflammation by motherwort based on network pharmacology, and relates to the technical field of medical treatment, which comprises the following steps: firstly, screening active components of motherwort from TCMSP and BATMAN-TCM databases through multi-dimensional data mining and interaction network modeling, and then predicting potential action targets of the active components by using SwisTargetPredictions and CTD databases; the method comprises the following steps: searching a target gene related to the CPID by utilizing two databases, namely a GeneCards database and an OMIM database; the method comprises the following steps: identifying common genes of active components such as quercetin of motherwort and a CPID target gene through a motherwort-target gene-CPID interaction network, and constructing a regulatory network by using Cytoscape software; according to the method, protein interaction network analysis is carried out by adopting an STRING database, in-depth analysis is carried out on network topology characteristics by applying Cytoscape, and function enrichment analysis (GO and KEGG) is carried out on key genes by adopting a cluster Profiler packet of an R language. A research result shows that the motherwort regulates and controls a plurality of key biological pathways and molecular processes through a multi-component and multi-target synergistic effect, so that the treatment effect of the motherwort on CPID is exerted.

Description

Technical Field

[0001] The present invention belongs to the field of medical technology, and specifically relates to a method for analyzing motherwort for treating chronic pelvic inflammatory disease based on network pharmacology, which is used to systematically analyze the multi-target mechanism of action of motherwort for treating chronic pelvic inflammatory disease. Background Art

[0002] Chronic pelvic inflammatory disease (CPID), a common chronic inflammatory disease in gynecology, is characterized by persistent lower abdominal pain, abnormal vaginal discharge, and reproductive dysfunction. Its pathogenesis involves an imbalance of multiple immune and inflammatory responses. Current clinical treatments face bottlenecks such as antibiotic resistance, surgical trauma, and the limitations of physical therapy, necessitating the exploration of novel therapeutic strategies.

[0003] Motherwort (Leonurus japonicus) has been used for thousands of years in the treatment of gynecological inflammation, but its multi-component, multi-target systemic mechanism of action remains largely unexplained. This study employed a network pharmacology approach to systematically explore the molecular mechanisms of action of motherwort in the treatment of chronic pelvic inflammatory disease (CPID). By constructing a "Motherwort-CPID" interaction network and analyzing its active components, target genes, and CPID-related pathways, the authors revealed a possible mechanism by which motherwort improves CPID, providing a scientific basis for its clinical application in the treatment of CPID. Summary of the Invention

[0004] To achieve the above objectives, the present invention is implemented by the following technical solutions: a method for treating chronic pelvic inflammatory disease with Leonurus japonicus based on network pharmacology analysis, the specific steps are as follows: S1: The basis of the efficacy of motherwort and the screening of target genes, Using the TCMSP platform (http: / / tcmspw.com), this study used Leonurus japonicus as the research target, setting dual screening criteria of oral bioavailability (OB ≥ 30%) and drug-likeness index (DL ≥ 0.18), successfully identifying eight active small molecules. To enhance data credibility, the chemical components were cross-validated using the BATMAN-TCM database (http: / / bionet.ncpsb.org.cn / batman-tcm / ). Subsequently, the SwissTargetPredictions (http: / / www.swisstargetprediction.ch / ) and CTD9 (https: / / ctdbase.org / ) databases were used to systematically identify the compound targets and construct a correspondence network between Leonurus japonicus components and their targets.

[0005] S2. Obtain target genes associated with CPID. Enter the keyword "Chronic Pelvic inflammatory disease" in the GeneCards platform (https: / / www.genecards.org / ) to obtain CPID-related target genes. Then, analyze the effect of these target genes on CPID in the OMIM database. Use a Venn diagram to cross-validate the two databases and remove duplicates to obtain the final list of CPID-related target genes.

[0006] S3. Construction of the Leonurus-Small Molecule-CPID Network Diagram: First, find the target genes corresponding to the active ingredients of Leonurus in the two databases and obtain the intersection. Finally, obtain the intersection of the target genes of the active ingredients of Leonurus and the target genes of CPID, thereby obtaining the Leonurus-Small Molecule-CPID Network Diagram, and use Cytoscape software to construct the Leonurus-Small Molecule-CPID Network Diagram. Finally, obtain the intersection of the target genes of Leonurus and the target genes of CPID. Visit the BioVenn website (https: / / www.biovenn.nl / ) and enter the target genes of Leonurus japonicus and CPID in the columns. Intersections of the target genes of Leonurus japonicus and CPID were taken, and a Venn diagram was drawn. Next, the common target genes of Leonurus japonicus and CPID were converted, and protein-protein interaction (PPI) analysis was performed using the STRING online tool. This study utilized the available protein-protein interaction (PPI) dataset and Cytoscape bioinformatics software to perform network topology analysis. According to the consensus of biological network theory, most biological system networks exhibit typical scale-free topological characteristics. Statistical analysis of node connectivity distribution can effectively identify core regulatory factors within interaction networks. Node topology analysis was performed on the constructed protein interaction network. Hub proteins were successfully identified based on the scale-free network properties, thereby revealing key biological functional units within the network's functional system.

[0007] S4. GO analysis and KEGG pathway enrichment analysis: Functional enrichment analysis was performed using the clusterProfiler toolkit in R. We systematically analyzed the regulatory characteristics of target genes in Leonurus herb for chronic pelvic inflammatory disease (CPID) across three dimensions: biological process (BP), cellular component (CC), and molecular function (MF). By screening the top 15 significantly enriched biological functions and disease-related signaling pathways in GO functional annotation and KEGG pathway analysis, we identified the core gene functional network and key metabolic pathways in Leonurus herb for CPID treatment, and further inferred its potential mechanism of action.

[0008] The present invention is based on network pharmacology and analyzes the treatment of CPID with Leonurus japonicus. Compared with the existing technology, it has the following advantages: A systems biology strategy was used to analyze the mode of action of the traditional Chinese medicine Leonurus japonicus. By constructing an interaction model of "Leonurus japonicus active ingredient-target gene-CPID", we aimed to reveal its multi-target and multi-pathway characteristics.

[0009] Conclusion: Motherwort targets multiple key molecules through the synergistic effect of its multiple components, participates in the regulation of a series of complex biological processes, thereby exerting multiple effects such as anti-inflammatory and damage repair, and ultimately achieving the purpose of treating CPID. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 ,Analysis flow chart of this research process; Figure 2 , Venn diagram showing the intersection of CPID target genes in GeneCards and OMIM databases; Figure 3 , Venn diagram of target genes of Leonurus japonicus and genes related to CPID; Figure 4 , target protein interaction network of Leonurus herb in treating CPID; Figure 5 , PPI network analysis of Leonurus japonicus in treating CPID; Figure 6 , GO biological process enrichment analysis diagram of the target gene provided by the present invention; Figure 7 , GOplot-circle diagram of target gene GO biological process enrichment analysis provided by the present invention; Figure 8 , KEGG pathway enrichment analysis diagram of the target gene provided by the present invention. DETAILED DESCRIPTION

[0011] Next, we will provide a complete and detailed description of the embodiments of the present invention with reference to the accompanying drawings. It should be noted that the examples described herein are only part of the present invention and not all examples. Based on these examples, all other examples that can be conceived by those skilled in the art without inventive work should be considered to be within the scope of the present invention. Example

[0012] The present invention uses a network pharmacology method to analyze the mechanism of Leonurus japonicus in treating CPID, which specifically includes the following steps: 1. Active components of Leonurus and their targets: Based on TCMSP, eight candidate molecules were identified by searching for the keyword "Leonurus" with oral bioavailability ≥ 30% and DL ≥ 0.18. Furthermore, 4,795 target genes were identified by searching the SwissTargetPredictions platform and the CTD database for target genes associated with active small molecules of Leonurus.

[0013] 2. By searching the "Chronic Pelvic inflammatory disease" entry in the GeneCards and OMIM databases, 5709 and 6086 relevant target genes were screened, respectively. After merging and deduplication, a total of 3212 pelvic inflammatory disease-associated genes were obtained, and finally standardized using the NCBI GENE database.

[0014] 3. Drawing of the Venn diagram of target genes of Leonurus japonicus and CPID First, we took the intersection of the target genes of Leonurus herb and CPID (a total of 1292 genes). We then performed PPI network analysis using the string online tool, screening for interaction pairs with a combined_score ≥ 0.9. We then used Cytoscape to construct a Leonurus herb-small molecule-CPID target gene network diagram.

[0015] 4. Prediction and analysis results of Leonurus japonicus-active ingredient small molecule-CPID target gene Based on the target gene dataset of Leonurus herb active ingredient-CPID, the interaction network diagram was constructed using Cytoscape software (version 3.10.3) ( Figure 3 Note: Rectangular nodes in the network diagram represent target genes, elliptical nodes correspond to active small molecules, and V-shaped nodes represent Leonurus japonicus.

[0016] 5. Protein interaction network This project intends to use TP53, SRC, EGFR, CTNNB1, and MAPK1 as research objects and use Cytoscape 3.10.3 software to draw a protein interaction network ( Figure 4), and the size and color of target genes were characterized using Degree and combinedscore. This led to the establishment of a protein interaction network centered around TP53, SRC, EGFR, CTNNB1, and MAPK1. TP53, a key transcription factor, mutations of which are closely associated with the development and progression of various cancers. Quercetin enhances decidualization of endometrial stromal cells through the AKT-ERK-p53 signaling pathway, suggesting a role for aging in endometriosis and providing a theoretical basis for related treatments. SRC, a tyrosine kinase, is involved in regulating key biological processes such as cell proliferation, differentiation, and signal transduction. Its dysfunction is significantly associated with the formation and progression of malignant tumors. The anti-inflammatory mechanisms of the active ingredients of Sargentophyllum cuneata and Patrinia patriniae against pelvic inflammatory disease were found to be through regulating the M1 / M2 phenotype switch and glucose metabolism. EGFR, a protein kinase composed of members of the epidermal growth factor (EGFR) family, binds to various growth factors, activates multiple signaling pathways, and regulates various life activities such as cell growth, proliferation, differentiation, and survival. Yinjia Tablets (YJP) have a potential pharmacological mechanism for reducing fallopian tube inflammation and promoting tissue repair by inhibiting the EGFR / MEK / ERK signaling pathway. CTNNB1, a core regulator of the WNT signaling pathway, has been found to be closely associated with the development and progression of numerous diseases. The role of miR-92b in Escherichia coli lipopolysaccharide (LPS)-induced endometritis has been shown to alleviate inflammatory damage by activating the PI3K / AKT / β-catenin pathway and inhibiting PTEN. MAPK1, a key regulatory molecule, plays a central role in cell proliferation, differentiation, and apoptosis.

[0017] GO gene biological process and KEGG signaling pathway enrichment analysis 6.1. GO gene biological process ( Figure 6 、 7 ) GO-KEGG analysis was performed using the clusterProfiler package (V4.16.0) in the R language (V4.5) on 1292 target genes of Leonurus herb and CPID. By filtering with a P-value < 0.01, we obtained a total of 6167 biological processes (BPs), 529 cellular components (CCs), and 902 molecular functions (MFs). BP enrichment suggested that Leonurus herb may play a role in the treatment of CPID by regulating responses to oxygen compounds, organic matter, and chemicals; cellular chemical stimuli; multicellular biological processes; responses to endogenous stimuli; programmed cell death; stress response; apoptosis regulation; and responses to organic nitrogen compounds. CC enrichment indicated the cytoplasm and its associated structures (cytoplasm, vesicles, cytoplasmic vesicles, intracellular vesicles) and the endomembrane system. MF-enriched functions included binding to cognate proteases, protein complexes, small molecules / ions / signaling receptors / proteins / anions, and binding to carbohydrate derivatives and various adenosine nucleotides / nucleotides (ATP).

[0018] 6.2 KEGG pathway enrichment analysis ( Figure 8 ) This patent uses the clusterProfiler software package in R language to conduct pathway enrichment analysis on target genes related to the intervention of motherwort in CPID. Based on P < 0.01, 145 pathways related to motherwort and the treatment of CPID were screened out, and the top 15 signal pathways were selected to make bubble charts, namely: the AGE-RAGE signaling pathway in diabetic patients, cell apoptosis, osteoclast differentiation, prostate cancer, human T-cell leukemia virus type 1 infection and other pathways.

[0019] This patent uses a network pharmacology approach to systematically elucidate the mechanism of action of Leonurus japonicus in the treatment of CPID. The research covers the drug's active ingredients, key targets, and related signaling pathways, providing theoretical support and research direction for subsequent in-depth studies.

[0020] The contents not described in detail in this specification can be regarded as common knowledge of ordinary technicians in the relevant technical field. The ordinal numbers such as "first" and "second" used in this article are only used to distinguish different objects or steps, and do not represent a sequence or logical relationship. In addition, the terms "include", "comprise" and their derivative forms all indicate non-exclusivity, which means that the relevant process, method, device or system may also cover other elements that are not explicitly stated or are common knowledge of those skilled in the art in addition to the listed components. In addition, the terms "include", "comprise" and their derivative forms all indicate non-exclusivity, which means that the relevant process, method, device or system may also cover other elements that are not explicitly stated or are common knowledge of those skilled in the art in addition to the listed components.

[0021] Although the present invention has been described through examples, those skilled in the art may make various modifications, substitutions, or variations without departing from the basic concepts and technical concepts of the present invention. The legal scope of a patent right is determined by the innovative contribution and equivalent technical features set forth in the claims.

[0022] Experimental data 1. Identification of active ingredients in Leonurus japonicus and prediction of their target genes based on database mining Based on this, multiple databases were used to screen for active ingredients in Leonurus japonicus. Based on TCMSP, a study of the basic principles of Chinese medicinal efficacy (with oral bioavailability ≥ 30% and drug-likeness index ≥ 0.18) was conducted, resulting in a preliminary screening of eight candidate active small molecules. Furthermore, the BATMAN-TCM platform was integrated to identify active small molecules. By combining the active small molecules from these two databases, a library of 27 compounds was established, including Gelegoside, Zinc04073977, and Quercetin.

[0023]

[0024] 2. Screening of CPID-related target genes CPID target gene screening was conducted using a combination of databases. Using the GeneCards database, the disease name "Chronic Pelvic inflammatory disease" was entered, initially yielding 5,709 candidate genes. Simultaneously, a search of the OMIM database for "Chronic Pelvic inflammatory disease" was performed for verification, yielding a total of 6,086 CPID-related entries. After deduplication and intersection analysis using BioVenn, a final set of 3,212 CPID-related target genes was obtained to ensure accuracy and reliability.

[0025] 3. Drawing of Venn diagram BioVenn software was used to intersect target genes associated with Leonurus herbaceous and CPID, yielding a total of 1,292 common genes. Protein-protein interaction (PPI) analysis was performed on these proteins using the STRING database, with a feasibility of ≥ 0.9. Cytoscape software was used to construct a "Leonurus herbaceous-active small molecule-CPID target gene" network diagram, identifying five core genes: TP53, SRC, EGFR, CTNNB1, and MAPK1.

[0026] 4. Drug-gene PPI network analysis On this basis, core genes were screened out based on the connectivity of each gene (the number of genes directly related to it).

[0027]

[0028] 5. Using the clusterProfiler package (V4.16.0) in R (V4.5), we performed functional annotation analysis on 1,292 key genes. This project included GO analysis (biological process, molecular biological function, and cellular component) and KEGG signaling pathway enrichment. A significance threshold (p < 0.01) was set, and the top 15 GO terms were plotted as histograms, while the top 15 KEGG terms were displayed as bubble charts.

Claims

1. A method for treating chronic pelvic inflammatory disease with Leonurus japonicus based on network pharmacology analysis, characterized in that: The specific steps include: S1: Screening of active ingredients of Leonurus japonicus and their target genes, First, systems pharmacology was used to screen the active ingredients of Leonurus japonicus. Original compound data was obtained by searching the TCMSP database. Using dual screening criteria (bioavailability ≥ 30%, drug-likeness ≥ 0.18), eight candidate active molecules were ultimately identified. To enhance data reliability, ingredient verification was performed using the BATMAN-TCM database. Subsequently, a component-target interaction network was constructed using the SwissTargetPrediction and CTD databases. S2: Acquisition of CPID target genes; Acquisition of CPID-related target genes, A multi-source database joint mining strategy was used to obtain disease-related genes: the keyword "Chronic Pelvic Inflammatory Disease" was searched based on the GeneCards database, and associated genes with Mendelian inheritance characteristics were screened using the clinical summary module of the OMIM database. Dual-library data were cross-validated using Venn diagram analysis, and UniProtID was used for normalization. Finally, a non-redundant gene set containing core pathogenic genes and potential regulatory factors was constructed. S3: Intersection of target genes of Leonurus japonicus and CPID target genes, Using the BioVenn online tool, the target gene lists of Leonurus and CPID were input respectively. The system will automatically generate and draw a Venn diagram of the targets of Leonurus and CPID. Subsequently, the common targets of Leonurus and CPID were extracted and converted into a format suitable for String platform analysis. Subsequently, the official website of the STRING database was visited, the species was selected as "homosapiens", and the common genes of these Leonurus and CPID were input to construct a protein interaction network (PPI) diagram, so as to further analyze the interaction relationship between the target proteins. S4: Gene Ontology (GO) analysis and KEGG pathway enrichment analysis: In order to functionally analyze the genes related to CPID: Based on the clusterProfiler package of R software, the core target genes were annotated with Gene Ontology (GO), covering cellular component (CC), molecular function (MF) and biological process (BP). KEGG pathway enrichment was performed simultaneously, and the significance threshold (p < 0.01) was set. The top 15 significant entries in GO ranking were screened, and the relevant verification pathways of CPID were located in combination with KEGG pathways. The "Motherwort-Active Small Molecule-CPID" multidimensional model was constructed using Cytoscape software to systematically explain the mechanism of action of Motherwort in treating CPID through key signaling pathways.

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