A System Pharmacology Model for Decoding the Synergistic Mechanisms of Compound Kushen Injection in Treating Breast Cancer

Breast cancer (BC) is one of the most common malignant tumors among women worldwide and can be treated using various methods; however, side effects of these treatments cannot be ignored. Increasing evidence indicates that compound kushen injection (CKI) can be used to treat BC. However, traditional Chinese medicine (TCM) is characterized by “multi-components” and “multi-targets”, which make it challenging to clarify the potential therapeutic mechanisms of CKI on BC. Herein, we designed a novel system pharmacology strategy using differentially expressed gene analysis, pharmacokinetics synthesis screening, target identification, network analysis, and docking validation to construct the synergy contribution degree (SCD) and therapeutic response index (TRI) model to capture the critical components responding to synergistic mechanisms of CKI in BC. Through our designed mathematical models, we defined 24 components as a high contribution group of synergistic components (HCGSC) from 113 potentially active components of CKI based on ADME parameters. Pathway enrichment analysis of HCGSC targets indicated that Rhizoma Heterosmilacis and Radix Sophorae Flavescentis could synergistically target the PI3K-Akt signaling pathway and the cAMP signaling pathway to treat BC. Additionally, TRI analysis showed that the average affinity of HCGSC and targets involved in the key pathways reached -6.47 kcal/mmol, while in vitro experiments proved that two of the three high TRI-scored components in the HCGSC showed significant inhibitory effects on breast cancer cell proliferation and migration. These results demonstrate the accuracy and reliability of the proposed strategy.

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Network Pharmacology-Based Prediction of the Active Ingredients and Potential Targets of Chinese Herbal Danyu Gukang Pills for Application to Osteonecrosis of the Femoral Head Disease

10.21203/rs.3.rs-143355/v1 ◽

2021 ◽

Author(s):

Yongchang Guo ◽

Dapeng Zhang ◽

Yuju Cao ◽

Xiaoyan Feng ◽

Caihong Shen ◽

...

Keyword(s):

Molecular Docking ◽

Femoral Head ◽

Signaling Pathway ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

In Vitro Experiments ◽

Active Components

Abstract Ethnopharmacological relevanceOsteonecrosis of the femoral head (ONFH) is still a challenge for orthopedists worldwide, which may lead to disability in patients without effective treatment. A newly developed formula of Chinese medicine, Danyu Gukang Pills (DGP), was recognized to be effective for ONFH. Nevertheless, its molecular mechanisms remain to be clarified. MethodsNetwork pharmacology was adopted to detect the mechanism of DGP on ONFH. The compounds of DGP were collected from the online databases, and active components were selected based on their OB and DL index. The potential proteins of DGP were acquired from TCMSP database, while the potential genes of ONFH were obtained from Gene Cards and Pubmed Gene databases. The function of Gene and potential pathways were researched by GO and KEGG pathway enrichment analysis. The compounds-targets and targets-pathways network were constructed in an R and Cytosacpe software. The mechanism was further investigated via molecular docking. Finally, in-vitro experiments were validated in the BMSCs. ResultsA total of 2305 compounds in DGP were gained, among which, 370 were selected as active components for which conforming to criteria. Combined the network analysis, molecular docking and in-vitro experiments, the results firstly demonstrated that the treatment effect of DGP on ONFH may be closely related to HIF-1α, VEGFA and HIF-1 signaling pathway. ConclusionThe current study firstly researched the molecular mechanism of DGP on ONFH based on network pharmacology. The results indicated that DGP may exert the effect on ONFH targeting on HIF-1α and VEGFA via HIF-1 signaling pathway.

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Ganghuo Kanggan Decoction in Influenza: Integrating Network Pharmacology and In Vivo Pharmacological Evaluation

Frontiers in Pharmacology ◽

10.3389/fphar.2020.607027 ◽

2020 ◽

Vol 11 ◽

Author(s):

Yanni Lai ◽

Qiong Zhang ◽

Haishan Long ◽

Tiantian Han ◽

Geng Li ◽

...

Keyword(s):

Signaling Pathway ◽

Influenza A ◽

Target Prediction ◽

Enrichment Analysis ◽

New Drugs ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Active Components ◽

Compound Screening

Background: Ganghuo Kanggan decoction (GHKGD) is a clinical experience prescription used for the treatment of viral pneumonia in the Lingnan area of China, and its clinical effect is remarkable. However, the mechanism of GHKGD in influenza is still unclear.Objective: To predict the active components and signaling pathway of GHKGD and to explore its therapeutic mechanism in influenza and to verified it in vivo using network pharmacology.Methods: The potential active components and therapeutic targets of GHKGD in the treatment of influenza were hypothesized through a series of network pharmacological strategies, including compound screening, target prediction and pathway enrichment analysis. Based on the target network and enrichment results, a mouse model of influenza A virus (IAV) infection was established to evaluate the therapeutic effect of GHKGD on influenza and to verify the possible molecular mechanism predicted by network pharmacology.Results: A total of 116 candidate active compounds and 17 potential targets were identified. The results of the potential target enrichment analysis suggested GHKGD may involve the RLR signaling pathway to reduce inflammation in the lungs. In vivo experiments showed that GHKGD had a protective effect on pneumonia caused by IAV-infected mice. Compared with the untreated group, the weight loss in the GHKGD group in the BALB/c mice decreased, and the inflammatory pathological changes in lung tissue were reduced (p < 0.05). The expression of NP protein and the virus titers in lung were significantly decreased (p < 0.05). The protein expression of RIG-I, NF-kB, and STAT1 and the level of MAVS and IRF3/7 mRNA were remarkably inhibited in GHKGD group (p < 0.05). After the treatment with GHKGD, the level of Th1 cytokines (IFN-γ, TNF-α, IL-2) was increased, while the expression of Th2 (IL-5, IL4) cytokines was reduced (p < 0.05).Conclusion: Through a network pharmacology strategy and in vivo experiments, the multi-target and multi-component pharmacological characteristics of GHKGD in the treatment of influenza were revealed, and regulation of the RLR signaling pathway during the anti-influenza process was confirmed. This study provides a theoretical basis for the research and development of new drugs from GHKGD.

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A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/6754761 ◽

2020 ◽

Vol 2020 ◽

pp. 1-18

Author(s):

Chunli Piao ◽

Qi Zhang ◽

De Jin ◽

Li Wang ◽

Cheng Tang ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Systems Pharmacology ◽

Active Components ◽

Kegg Pathways

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

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Network Pharmacological Analysis of Huanglian Jiedu Decoction for Anti- Atherosclerosis

10.21203/rs.3.rs-44241/v1 ◽

2020 ◽

Author(s):

Kerui Wu ◽

Lu Jiang ◽

Lanlin Huang ◽

Yaxing He ◽

Xia Yan ◽

...

Keyword(s):

Signaling Pathways ◽

Signaling Pathway ◽

Fluid Shear Stress ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Active Ingredients ◽

Active Components ◽

Protein Protein Interaction ◽

Target Regulation

Abstract Objective: We aimed to predict the possible active components,key targets and pathways of Huanglian Jiedu Decoction(HLJDD) for anti-atherosclerosis. Methods: The TCMSP database was searched to obtain the active components and targets of HLJDD, the GeneCards and OMIM databases were searched to obtain related targets of atherosclerosis, and we obtain the intersection targets of them, which are the potential targets of HLJDD for anti-atherosclerosis.Application of Cytoscape 3.6.0 software to build a herbal-active ingredient-potential target regulation network.We perform protein-protein interaction(PPI) network analysis of potential targets through STRING 11.0 database and obtain the key targets,and the results of PPI network of key targets were visualized by Cytoscape3.6.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the key targets were performed using STRING11.0 database, and we finally constructed the possible pharmacological network of HLJDD for anti-atherosclerosis .Results: We finally obtained 14 key active ingredients of HLJDD, 65 key targets of anti-atherosclerosis, and 14 key active ingredients corresponded to 52 of these targets. These targets are mainly involved in biological processes such as reaction to organic substance, reaction to chemical stimulation,etc.They mainly involved in biological signaling pathways such as pathways in cancer,IL-17 signaling pathway,etc. Conclusion: HLJDD may act on 52 key targets such as PTGS2, HSP90AA1 and RELA through 14 key active ingredients, and influence the signaling pathways including fluid shear stress and atherosclerosis,PI3K-Akt signaling pathway,IL-17 signaling pathway,AGE-RAGE signaling pathway in diabetic complications,TNF signaling pathway,etc.Thus, it may play an anti-atherosclerosis role by inhibiting inflammatory reaction, oxidative stress and improving hemodynamics,etc.

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Elaborate the Mechanism of Ancient Classic Prescriptions (Erzhi Formula) in Reversing GIOP by Network Pharmacology Coupled with Zebrafish Verification

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2022/7019792 ◽

2022 ◽

Vol 2022 ◽

pp. 1-17

Author(s):

Zhihui Cai ◽

Huajun Wang ◽

Jun Jiang ◽

Shichang Xiao ◽

Jianpeng Xiao ◽

...

Keyword(s):

Signaling Pathway ◽

Optical Density ◽

Bone Mineralization ◽

Enrichment Analysis ◽

Akt Signaling ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Akt Signaling Pathway ◽

Active Components ◽

Zebrafish Model

Osteoporosis is a degenerative disease that endangers human health. At present, chemical drugs used for osteoporosis have serious side effects. Therefore, it is valuable to search herbs with high safety and good curative effect in antiosteoporosis. Erzhi formula (EZF), an ancient classic compound, has been reported to have a beneficial effect in antiosteoporosis, but its mechanism is unclear. In this paper, the active compounds of EZF were found in Systems Pharmacology Database, and gene targets related to osteoporosis were obtained in GeneCards. The GO functional and KEGG pathway enrichment analysis were performed by Metascape. The network of “components-targets-signal pathway” was constructed by Cytoscape. Next, molecular docking between the active components and hub genes related to the PI3K-Akt signaling pathway was conducted by Autodock. In the verification experiment, the zebrafish induced by prednisolone (PNSL) was used to reproduce glucocorticoid-induced osteoporosis (GIOP) model, and then the reversal effects of EZF were systematically evaluated according to the behavior, skull staining area, bone mineralization area (BMA), average optical density (AOD), and cumulative optical density (COD). Finally, it was shown that 24 components in EZF could regulate 39 common gene targets to exert antiosteoporosis effect. Besides, the main regulatory mechanisms of EZF were 4 signaling pathways: PI3K-Akt, JAK-STAT, AGE-RAGE, and cancer pathway. In PI3K-Akt signaling pathway, wedelolactone, dimethyl wedelolactone, specnuezhenide, ursolic acid, acacetin, beta-sitosterol, apigenin, and kaempferol can bind tightly with EGF, IL-2, and IL-4 genes. Compared with the model group, the moving distance, swimming speed, and cumulative swimming time of zebrafish in EZF group were significantly increased ( P < 0.05 ). Meanwhile, the BMA and COD of zebrafish were significantly improved after the intervention of EZF ( P < 0.05 ). In summary, the 24 components of EZF exert their antiosteoporosis effects by regulating 39 related gene targets, among which the PI3K signaling pathway is crucial. EZF can promote bone formation and reversed GIOP through “multicomponent/multitarget/multipathway” and the medium dose of EZF may be the most suitable concentration for the treatment of GIOP in zebrafish model.

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Identification of FEZ2 as a potential oncogene in pancreatic ductal adenocarcinoma

PeerJ ◽

10.7717/peerj.12736 ◽

2022 ◽

Vol 9 ◽

pp. e12736

Author(s):

Chaozhi Yang ◽

Xuebing Wang ◽

Chenjie Qiu ◽

Ziruo Zheng ◽

Kai Lin ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Cancer Progression ◽

Poor Prognosis ◽

Malignant Tumors ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Ductal Adenocarcinoma ◽

Pathway Enrichment Analysis ◽

Conserved Gene

Pancreatic ductal adenocarcinoma (PDAC) is one of the common malignant tumors with high lethal rate and poor prognosis. Dysregulation of many genes have been reported to be involved in the occurrence and development of PDAC. However, as a highly conserved gene in eukaryotes, the role of Fasciculation and Elongation protein Zeta 2 (FEZ2) in pancreatic cancer progression is not clear. In this study, we identified the oncogenic effect of FEZ2 on PDAC. By mining of The Cancer Genome Atlas (TCGA) database, we found that FEZ2 was upregulated in PDAC tissues and FEZ2 expression was negatively regulated by its methylation. Moreover, high expression and low methylation of FEZ2 correlated with poor prognosis in PDAC patients. Besides, we found that FEZ2 could promote PDAC cells proliferation, migration and 5-FU resistance in vitro. Furthermore, Gene pathway enrichment analysis demonstrated a positive correlation between Wnt signaling activation and FEZ2 expression in PDAC patients. Western blot showed that FEZ2 knockdown significantly suppressed β-catenin expression. Collectively, our finding revealed that FEZ2 functioned as a potential oncogene on PDAC progression and migration, and the expression of FEZ2 had guidance value for the treatment and chemotherapy program of PDAC patients.

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Upregulation of FEN1 Is Associated with the Tumor Progression and Prognosis of Hepatocellular Carcinoma

Disease Markers ◽

10.1155/2020/2514090 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Yingying Zhang ◽

Xin Liu ◽

Liwen Liu ◽

Jianan Chen ◽

Qiuyue Hu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Molecular Mechanisms ◽

Cox Regression ◽

Malignant Tumors ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Functional Roles ◽

Protein Levels ◽

And Migration

Background. Studies show that patients with hepatocellular carcinoma (HCC) have poor prognosis, particularly when patients are diagnosed at late stages of the disease development. The flap endonuclease 1 (FEN1) gene is overexpressed in multiple malignant tumors and may promote tumor aggressiveness. However, its expression profile and functional roles in HCC are still unclear. Here, we evaluated the molecular mechanisms of FEN1 in HCC. Methods. The expression of FEN1 in HCC was evaluated using HCC mRNA expression data from TCGA and GEO databases. The expression of FEN1 was also confirmed by immunohistochemistry (IHC) using a tissue microarray (TMA) cohort with a total of 396 HCC patients. Kaplan-Meier analysis and univariate and multivariate Cox regression analyses were used to determine the correlation between FEN1 expression and survival rate of HCC patients. The molecular mechanism and biological functions of FEN1 in HCC were predicted using functional and pathway enrichment analysis in vitro experiments. Results. FEN1 was overexpressed in multiple HCC cohorts at both mRNA and protein levels. The receiver operating characteristic (ROC) curve showed that FEN1 can serve as a diagnostic predictor of HCC. Meanwhile, patients with high FEN1 expression levels showed lower overall survival (OS) and relapse-free survival (RFS) rates than those with low FEN1 expression. More importantly, we found that FEN1 elevation was an independent prognostic factor for OS and RFS in HCC patients based on univariate and multivariate analyses, indicating that FEN1 might be a potential prognostic marker in HCC. Furthermore, knocking down FEN1 resulted in suppressed cell proliferation and migration in vitro. This could have been due to regulation expressions of c-Myc, survivin, and cyclin D1 genes, indicating that FEN1 may function as an oncogene through its role in the cell cycle and DNA replication pathway. Conclusion. Our study indicated that high FEN1 expression might function as a biomarker for diagnosis and prognosis. In addition, the study confirms that FEN1 is an oncogene in HCC progression.

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A Network Pharmacology Study Based on the Mechanism of Citri Reticulatae Pericarpium-Pinelliae Rhizoma in the Treatment of Gastric Cancer

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6667560 ◽

2021 ◽

Vol 2021 ◽

pp. 1-17

Author(s):

Siyuan Song ◽

Wenjie Huang ◽

Xiaona Lu ◽

Jiatong Liu ◽

Jiayu Zhou ◽

...

Keyword(s):

Gastric Cancer ◽

Ferulic Acid ◽

Signaling Pathway ◽

Octadecenoic Acid ◽

Enrichment Analysis ◽

Signal Pathway ◽

Pathway Enrichment Analysis ◽

Biological Processes ◽

Active Components ◽

Vascular Regeneration

Objective. To explore the mechanism of action of Citri Reticulatae Pericarpium-Pinelliae Rhizoma (CRP-PR) in treating gastric cancer (GC) by using pharmacology network. Methods. Based on oral bioavailability and drug-likeness, the main active components of CRP-PR were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). DisGeNET Database was used to establish target databases for GC. Cytoscape software was used to construct a visual interactive network diagram of “Active Component-Target” and screen out the key targets. The STRING database was used to construct a protein interaction network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the key targets. Additionally, TCGA and HPA databases were used for key target verification. Results. Thirty-seven active components of CRP-PR were screened. The results of network analysis showed that the main components include 8-octadecenoic acid, stigmasterol, ferulic acid, and naringenin of the CRP-PR herb pair. The key targets of the PPI network mainly involved GAPDH, MAPK3, JUN, STAT3, GSK3B, SIRT1, ERBB2, and SMAD2. GO enrichment analysis involves 540 biological processes, 118 cellular components, and 171 molecular functions. CRP-PR components were predicted to exert their therapeutic effect on the tumor signaling pathway, PI3K-Akt signaling pathway, MAPK signaling pathway, and estrogen signaling pathway. The validation of the key genes in the TCGA and HPA database showed that most of the key target verification results were consistent with this article. Conclusion. CRP-PR can treat GC by mediating PI3K-Akt signal pathway, MAPK signal pathway, and other biological processes such as tumor cell proliferation, apoptosis, and vascular regeneration, which embodies the synergistic effect of multi-components, multi-targets, and multi-channels, and provides the theoretical basis and research ideas for further study of CRP-PR in treating GC. 8-octadecenoic acid, stigmasterol, ferulic acid, and naringenin may be the material basis for the treatment of GC.

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Study on the mechanism of Erzhi Pill in the treatment of breast cancer based on network pharmacology

E3S Web of Conferences ◽

10.1051/e3sconf/202124503055 ◽

2021 ◽

Vol 245 ◽

pp. 03055

Author(s):

Fahu Yuan ◽

Xinghua Liao ◽

Tongcun Zhang

Keyword(s):

Breast Cancer ◽

Target Genes ◽

Enrichment Analysis ◽

Suppressor Gene ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Active Components ◽

Annotation Database ◽

Amino Terminal ◽

Target Network

Objective: To explore the possible mechanism of Erzhi Pill in the treatment of breast cancer based on network pharmacology. Methods: Through systematic pharmacology database and analysis platform of Traditional Chinese medicine (TCMSP) and literature review, the candidate active ingredients and corresponding targets of Erzhi Pill were retrieved and collected. The UniProt database and the Human Genome Annotation Database (Genecards) were used to compare the results, and the potential target genes were obtained for the coincidence of Erzhi Pill and breast cancer. Cytoscape was used to construct the “candidate component - action target” network of Erzhi Pill. Generate Style from Statistics tool in String database and Cytoscape software was combined to construct protein interaction network.The Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis and GO classification enrichment analysis for targets of Erzhi Pill were conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID ) bioinformation resource Database. Results: A total of 21 candidate active components, including Beta-sitosterol, Quercetin, Luteolin, Demethylwedelolactone, Kaempferol and so on, were screened from Erzhi Pill, corresponding to 158 target genes, including vascular endothelial growth factor (VEGF), amino-terminal kinase (C-Jun), proto-oncogene (C-MYC), matrix metalloproteinase-9 (MMP-9), and mainly involved in TNF-α, phosphatidylinositol-3-kinase/protein kinase B(PI3K/Akt), tumor suppressor gene p53, toll-like receptor family and other signaling pathways. Conclusion: This study predicted the possible mechanism of action of Erzhi Pill in the treatment of breast cancer based on the method of network pharmacology, and provided a direction for further research.

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A Bioinformatics Research on Novel Mechanism of Compound Kushen Injection for Treating Breast Cancer by Network Pharmacology and Molecular Docking Verification

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/2758640 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Shuyu Liu ◽

Xiaohong Hu ◽

Xiaotian Fan ◽

Ruiqi Jin ◽

Wenqian Yang ◽

...

Keyword(s):

Breast Cancer ◽

Molecular Docking ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Binding Activity ◽

Active Compounds ◽

Strong Binding ◽

Target Network ◽

Compound Kushen Injection ◽

Strong Binding Activity

Compound Kushen injection (CKI) has been extensively used in treating breast cancer (BC). However, the molecular mechanism remains unclear. In this study, 16 active compounds of CKI were obtained from 3 articles for target prediction. Then, a compound-predicted target network and a compound-BC target network were conducted by Cytoscape 3.6.1. The gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the DAVID database. The binding energy between the key targets of CKI and the active compounds was studied by molecular docking. As a result, 16 active compounds of CKI were identified, corresponding to 285 putative targets. The key targets of CKI for BC are HSD11B1, DPP4, MMP9, CDK1, MMP2, PTGS2, and CA14. The function enrichment analysis obtained 13 GO entries and 6 KEGG pathways, including bladder cancer, cancer pathways, chemical carcinogenesis, estrogen signaling pathway, TNF signaling pathway, and leukocyte transendothelial migration. The result of molecular docking indicated that DPP4 had strong binding activity with matrine, alicyclic protein, and sophoridine, and MMP9 had strong binding activity with adenine and sophoridine. In conclusion, the therapeutic effect of CKI on BC is based on the overall pharmacological effect formed by the combined effects of multiple components, multiple targets, and multiple pathways. This study provides a theoretical basis for further experimental research in the future.

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