scholarly journals Bioinformatics Analysis to Screen Key Targets of Curcumin against Colorectal Cancer and the Correlation with Tumor-Infiltrating Immune Cells

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xinyue Han ◽  
Chao Yang ◽  
Cui Guo ◽  
Yimin Xu ◽  
Xiaoqiang Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Protein Kinase Activity

Purpose. Curcumin is a potential drug for the treatment of colorectal cancer (CRC). Its mechanism of action has not been elucidated. This study aims to investigate the mechanism of action of curcumin in the treatment of CRC via bioinformatics methods such as network pharmacology and molecular docking. Methods. The targets of curcumin and CRC were obtained from the public databases. The component-targets network of curcumin in the treatment of CRC was constructed by Cytoscape v3.7.2. Through protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG), important targets and signaling pathways related to CRC treatment were identified. Finally, the results were verified by molecular docking, and the correlation between the key targets and tumor-infiltrating immune cells (TICs) was analyzed. Results. A total of 30 potential targets of curcumin for CRC treatment were collected. The GO function enrichment analysis showed 140 items, and the KEGG pathway enrichment analysis showed 61 signaling pathways related to the regulation of protein kinase activity, negative regulation of apoptosis process, cancer signaling pathway, and PI3K-Akt signaling pathway. The molecular docking results showed that curcumin could be combined with AKT1, EGFR, and STAT3 more stably, and AKT1 has the strongest binding to curcumin. Bioinformatics analysis discovered that the expression of core targets AKT1, EGFR, and STAT3 in CRC was related to TICs. Conclusion. This study explored the targets and pathways of curcumin in the treatment of CRC. The core targets are AKT1, EGFR, and STAT3. The study indicated that curcumin has preventive and treatment effects on CRC through multitarget and multipathway, which laid the foundation for follow-up research.

scholarly journals Systematic Elucidation of the Mechanism of Action of Curcumin Against Colorectal Cancer via Network Pharmacology Approach

2021 ◽  
Author(s):  
Xinyue Han ◽  
Yimin Xu ◽  
Xiaoqiang Liu ◽  
Yuan Li ◽  
Cui Guo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Experimental Verification ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
In Vitro Experiments

Abstract Background: Curcumin is a potential drug for the treatment of colorectal cancer (CRC). Its mechanism of action has not been elucidated.Aim: To investigate the mechanism of action of curcumin in the treatment of CRC via network pharmacology, molecular docking and experimental verification.Methods: The targets of curcumin and CRC were obtained from the public databases. The component-targets network of curcumin in the treatment of CRC was constructed by Cytoscape v3.7.2. Through protein-protein interaction (PPI), the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), important targets and signaling pathways related to CRC treatment were identified. Finally, the results were verified by molecular docking and in vitro experiments.Results: A total of 30 potential targets of curcumin for CRC treatment were collectedThe core targets included AKT1, EGFR and STAT3 were identified. GO function enrichment analysis showed 140 items, and KEGG pathway enrichment analysis showed 61 signaling pathways, that were related to the regulation of protein kinase activity, negative regulation of apoptosis process, cancer signaling pathway and PI3K-Akt signali-ng pathway. In vitro experimental verification showed that curcumin could promote the apoptosis of CRC cells, and the key proteins of these signaling pathways were differentially expressed.Conclusion: This study explored the targets and pathways of curcumin in the treatment of colorectal cancer. In vitro experiments showed that curcumin has a therapeutic effect against CRC by inhibiting PI3K-Akt signaling pathway. Our results will lay a foundation for subsequent clinical research and drug development.

scholarly journals Network Pharmacology Study and Molecular Docking on the Mechanism of Treatment of Colorectal Cancer by Xiao-Chai-Hu-Tang

2021 ◽  
Author(s):  
Jingyun Jin ◽  
Bin Chen ◽  
Xiangyang Zhan ◽  
Zhiyi Zhou ◽  
Hui Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gene Ontology ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Active Ingredients ◽  
Pathway Gene

Abstract Background and objective: To predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, to further analyze its anti-CRC material basis and mechanism of action.Methods: TCMSP and TCMID databases were adopted to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The above common targets were used to construct the “herb-active ingredients-target” network by Cytoscape 3.8.0 software. And then, the protein-to-protein interaction（PPI）was constructed and analyzed with BisoGenet and CytoNCA plug-in in Cytoscape. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were then performed using the R package of cluster Profiler. Further, AutoDock Vina software was used to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results.Results: A total of 71 active ingredients of XCHT and 20 potential targets for anti-CRC were identified. The network analysis revealed that quercetin, stigmasterol, kaempferol, baicalein, acacetin may be the key compounds. And PTGS2, NR3C2, CA2, MMP1 may be the key targets. The active ingredients of XCHT interacted with most disease targets of CRC. It fully showed that XCHT exerted its therapeutic effect through the synergistic action of the multi-compound, multi-target, and multi-pathway. Gene ontology enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. 11 KEGG signaling pathways had been identified, including IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and NF-kappa B signaling pathway. It showed that XCHT played a role in the treatment of CRC by regulating different signal pathways. Molecular docking confirmed the correlation between five core compounds (including quercetin, stigmasterol, kaempferol, baicalein, and acacetin) and PTGS2.Conclusion: The potential active ingredients, possible targets, and key biological pathways for the efficacy of XCHT in the treatment of CRC were preliminarily described, which provided a theoretical basis for further experimental verification research.

scholarly journals Bioinformatics analysis and identification of genes and molecular pathways in steroid-induced osteonecrosis of the femoral head

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Tianye Lin ◽  
Weijian Chen ◽  
Peng Yang ◽  
Ziqi Li ◽  
Qiushi Wei ◽  
...  
Keyword(s):  
Femoral Head ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Peripheral Blood ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Qrt Pcr

Abstract Background Steroid-induced osteonecrosis of the femoral head (ONFH) is a common hip joint disease and is difficult to be diagnosed early. At present, the pathogenesis of steroid-induced ONFH remains unclear, and recognized and effective diagnostic biomarkers are deficient. The present study aimed to identify potentially important genes and signaling pathways involved in steroid-induced ONFH and investigate their molecular mechanisms. Methods Microarray data sets GSE123568 (peripheral blood) and GSE74089 (cartilage) were obtained from the Gene Expression Omnibus database, including 34 ONFH samples and 14 control samples. Morpheus software and Venn diagram were used to identify DEGs and co-expressed DEGs, respectively. Besides, we conducted Kyoto Encyclopedia of Genome (KEGG) and gene ontology (GO) pathway enrichment analysis. We construct a protein-protein interaction (PPI) network through GEO2R and used cytoHubba to divide the PPI network into multiple sub-networks. Additionally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the bioinformatics analysis results. Results A total of 118 intersecting DEGs were obtained between the peripheral blood and cartilage samples, including 40 upregulated genes and 78 downregulated genes. Then, GO and KEGG pathway enrichment analysis revealed that upregulated DEGs focused on the signaling pathways related to staphylococcus aureus infection, leishmaniasis, antigen processing, and presentation, as well as asthma and graft-versus-host disease. Downregulated genes were concentrated in the FoxO signaling pathway, AMPK signaling pathway, signaling pathway regulating stem cell pluripotency, and mTOR signaling pathway. Some hub genes with high interactions such as CXCR1, FPR1, MAPK1, FOXO3, FPR2, CXCR2, and TYROBP were identified in the PPI network. The results of qRT-PCR demonstrated that CXCR1, FPR1, and TYROBP were upregulated while MAPK1 was downregulated in peripheral blood of steroid-induced ONFH patients. This was consistent with the bioinformatics analysis. Conclusions The present study would provide novel insight into the genes and associated pathways involved in steroid-induced ONFH. CXCR1, FPR1, TYROBP, and MAPK1 may be used as potential drug targets and biomarkers for the diagnosis and prognosis of steroid-induced ONFH.

scholarly journals The G Protein-Coupled Estrogen Receptor (GPER) Expression Correlates with Pro-Metastatic Pathways in ER-Negative Breast Cancer: A Bioinformatics Analysis

Cells ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 622 ◽  
Author(s):  
Marianna Talia ◽  
Ernestina De Francesco ◽  
Damiano Rigiracciolo ◽  
Maria Muoio ◽  
Lucia Muglia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Signaling Pathways ◽  
G Protein ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
G Protein Coupled

The G protein-coupled estrogen receptor (GPER, formerly known as GPR30) is a seven-transmembrane receptor that mediates estrogen signals in both normal and malignant cells. In particular, GPER has been involved in the activation of diverse signaling pathways toward transcriptional and biological responses that characterize the progression of breast cancer (BC). In this context, a correlation between GPER expression and worse clinical-pathological features of BC has been suggested, although controversial data have also been reported. In order to better assess the biological significance of GPER in the aggressive estrogen receptor (ER)-negative BC, we performed a bioinformatics analysis using the information provided by The Invasive Breast Cancer Cohort of The Cancer Genome Atlas (TCGA) project and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. Gene expression correlation and the statistical analysis were carried out with R studio base functions and the tidyverse package. Pathway enrichment analysis was evaluated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the Database for Annotation, Visualization and Integrated Discovery (DAVID) website, whereas gene set enrichment analysis (GSEA) was performed with the R package phenoTest. The survival analysis was determined with the R package survivALL. Analyzing the expression data of more than 2500 primary BC, we ascertained that GPER levels are associated with pro-migratory and metastatic genes belonging to cell adhesion molecules (CAMs), extracellular matrix (ECM)-receptor interaction, and focal adhesion (FA) signaling pathways. Thereafter, evaluating the disease-free interval (DFI) in ER-negative BC patients, we found that the subjects expressing high GPER levels exhibited a shorter DFI in respect to those exhibiting low GPER levels. Overall, our results may pave the way to further dissect the network triggered by GPER in the breast malignancies lacking ER toward a better assessment of its prognostic significance and the action elicited in mediating the aggressive features of the aforementioned BC subtype.

scholarly journals Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Mengshi Tang ◽  
Xi Xie ◽  
Pengji Yi ◽  
Jin Kang ◽  
Jiafen Liao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Binding Activity ◽  
New Combination ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

scholarly journals A competing endogenous RNA mechanism in glioblastoma is investigated by bioinformatics analysis

2020 ◽  
Author(s):  
Jinsheng Wang ◽  
Yutao Wang ◽  
Lei Gao ◽  
Yuhua Zhao ◽  
Junhua Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Lupus Erythematosus ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Dendritic Cell Maturation ◽  
Vital Role ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
P53 Signaling

Abstract Background Glioblastoma (GBM) is the most aggressive and most lethal primary malignant brain tumor, the 5-year survival rate of which is less than 5%. Novel potential molecular and mechanism of GBM need to investigate.Materials and methods Microarray data of GSE15824 was downloaded from GEO. Differentially expressed genes and lncRNAs were screened by Limma package in R studio, and pathway enrichment analysis was performed by clusterprofiler package in R studio and IPA. The ceRNA mechanism was analyzed and predicted by several kinds of online public databases.ResultsThere were 567 differentially expressed genes and 121 differentially expressed lncRNAs in GBM. And differentially expressed genes were mainly enriched in Tuberculosis, Staphylococcus aureus infection, Systemic lupus erythematosus, Basal cell carcinoma, TGF-beta signaling pathway and p53 signaling pathway. Besides, Neuroinflammation signaling pathway, Role of NFAT in regulation of the immune response, and Dendritic cell maturation were significantly activated in GBM. According to the analysis of target miRNAs of SEM4D and OSER1-AS1, a possible ceRNA mechanism OSER1-AS1/hsa-miR-520h/SEMA4D axis was predicted in GBM.Conclusion Bioinformatics analysis was employed to analyze GSE15824 chip, and predict the potential mechanism. The results revealed that the ceRNA mechanism, OSER1-AS1/hsa-miR-520h/SEMA4D axis, might play a vital role in GBM.

scholarly journals Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology and molecular docking

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Core Proteins ◽  
Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

scholarly journals Exploring the Mechanism of Quercetin for the Treatment of Atrial Fibrillation by Geo Gene Chip Combined With Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
tan xin ◽  
Wei Xian ◽  
Xiaorong Li ◽  
Yongfeng Chen ◽  
Jiayi Geng ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Chemical Structures ◽  
Drug Mechanism

Abstract PurposeAtrial fibrillation (AF) is a common atrial arrhythmia. Quercetin (Que) has some advantages in the treatment of cardiovascular disease arrhythmias, but its specific drug mechanism of action needs further investigation. To explore the mechanism of action of Que in AF, core target speculation and analysis were performed using network pharmacology and molecular docking methods.MethodsQue chemical structures were obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank , STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF from normal tissues by GEO database differentially expressed genes. Then, the intersecting genes were obtained by online Wayne mapping tool. The intersection genes were introduced into the top five targets selected for molecular docking via protein-protein interaction (PPI) network to verify the binding activity between Que and the target proteins. GO and KEGG enrichment analysis of the intersected genes using program R was performed to further screen for key genes and key pathways.ResultsThere were 65 effective targets for Que and AF. Through further screening, the top 5 targets were IL6, VEGFA, JUN, MMP9 and EGFR. Que treatment of AF may involve signaling pathways such as lipid and atherosclerosis pathway, AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. Molecular docking suggests that Que has strong binding to key targets.ConclusionThis study systematically elucidates the key targets of Que treatment for AF and the specific mechanisms through network pharmacology as well as molecular docking, providing a new direction for further basic experimental exploration and clinical treatment.

scholarly journals Deciphering Expression Profiling and Functional Signatures of Individualized Obesity-Associated Genes in Ossification of Ligamentum Flavum Through RNA-Sequence Data Mining

2021 ◽  
Author(s):  
Baoliang Zhang ◽  
Lei Yuan ◽  
Guanghui Chen ◽  
Xi Chen ◽  
Xiaoxi Yang ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Immune Cells ◽  
Ligamentum Flavum ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Ossification Of Ligamentum Flavum

Abstract Background: Obese individuals predispose to ossification of ligamentum flavum (OLF), whereas the underlying connections between obesity phenotype and OLF pathomechanism are not fully understood, especially during early life. This study aimed to explore obesity-associated genes and their functional signatures in OLF. Methods: Gene microarray expression data related to OLF were downloaded from the GSE106253 dataset in the Gene Expression Omnibus (GEO) database. The potential obesity-related differentially expressed genes (ORDEGs) in OLF were screened. Then, gene-ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied for these genes. Furthermore, protein-protein interactions (PPI) were used to identify hub ORDEGs, and Metascape was used to further verify the key signaling pathways and immune-related function signatures of hub ORDEGs. Finally, correlation analysis of hub ORDEGs and identified OLF-related infiltrating immune cells (OIICs) was constructed to understand the possible mechanical link among obesity, immune response and OLF. Results: OLF-related differentially expressed genes and 2051 obesity-related genes from four databases were intersected to obtain 99 ORDEGs, including 54 upregulated and 55 downregulated genes. GO and KEGG analysis revealed that these genes were mainly involved in metabolism, inflammation and immune-related biological functions and pathways. A PPI network was established to determine 14 hub genes (AKT1, CCL2, CCL5, CXCL2, ICAM1, IL10, MYC, PTGS2, SAA1, SOCS1, SOCS3, STAT3, TNFRSF1B and VEGFA). The co-expression network demonstrated that this module was associated with cellular response to biotic stimulus, regulation of inflammatory response, regulation of tyrosine phosphorylation of STAT protein. Furthermore, Metascape functional annotations showed that hub genes were mainly involved in receptor signaling pathway via JAK-STAT, response to TNF and regulation of defense response, and their representative enriched pathways were TNF, adipocytokine and JAK-STAT signaling pathways. Subgroup analysis indicated that T cell activation might be potential immune function processes involved, and correlation analysis revealed that cDCs, memory B-cells and preadipocytes were highly correlated infiltrating immune cells. Conclusions: Our study deciphered individualized obesity-associated gene signature for the first time, which may facilitate exploring the underlying cellular and molecular pathogenesis and novel therapeutic targets of obesity-related early-onset OLF.

scholarly journals Integrating Network Pharmacology and Experimental Validation Deciphers the Mechanism of Guizhi Fuling Wan against Adenomyosis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Haoxian Wang ◽  
Jihong Zhang ◽  
Qinqin Zhu ◽  
Xianyun Fu ◽  
Chenjie Li
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Animal Experiments ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Verification Methods

Aim. This study aimed to predict the key targets and endocrine mechanisms of Guizhi Fuling Wan (GZFLW) in treating adenomyosis (AM) through network pharmacology, molecular docking, and animal experiment verification. Methods. The related ingredients and targets of GZFLW in treating AM were screened out using TCMSP, BATMAN-TCM, SwissTargetPrediction, and PubChem Database. Then, the protein-protein interaction (PPI) analysis and the network of compound-hub targets were constructed. At the same time, the key targets were uploaded to the Metascape Database for KEGG pathway enrichment analysis. After that, the molecular docking technology of the main active components and hub targets was performed. Furthermore, animal experiments were used to verify the results of network pharmacology analysis. Results. A total of 55 active ingredients of GZFLW and 44 overlapping targets of GZFLW in treating AM were obtained. After screening, 25 hub targets were collected, including ESR1, EGF, and EGFR. Then, the KEGG pathway enrichment analysis results indicated that the endocrine therapeutic mechanism of GZFLW against AM is mainly associated with the estrogen signaling pathway, endocrine resistance, and an EGFR tyrosine kinase signaling pathway. Then, molecular docking showed that the significant compounds of GZFLW had a strong binding ability with ERα and EGFR. More importantly, the animal experiments confirmed that the GZFLW could downregulate the abnormal infiltration of the endometrial epithelium into the myometrium and had no interference with the normal sexual cycle. This effect may be directly related to intervening the local estrogen signaling pathway of the endometrial myometrial interface (EMI). It may also be associated with the myometrium cells’ estrogen resistance via GPER/EGFR signaling pathway. Conclusion. The endocrine mechanism of GZFLW in treating AM was explored based on network pharmacology, molecular docking, and animal experiments, which provided a theoretical basis for the clinical application of GZFLW.

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