scholarly journals A Network Pharmacology Technique to Investigate the Synergistic Mechanisms of Salvia miltiorrhiza and Radix puerariae in Treatment of Cardio-Cerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Yang Ma ◽  
Wenjun Wang ◽  
Jiani Yang ◽  
Sha Zhang ◽  
Zhe Li ◽  
...  
Keyword(s):  
Drug Targets ◽  
Salvia Miltiorrhiza ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Radix Puerariae ◽  
Cerebral Vascular

Objective. This study is aimed to analyze the active ingredients, drug targets, and related pathways in the combination of Salvia miltiorrhiza (SM) and Radix puerariae (RP) in the treatment of cardio-cerebral vascular diseases (CCVDs). Method. The ingredients and targets of SM and RP were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the disease targets were obtained from Therapeutic Target Database (TTD), National Center for Biotechnology Information (NCBI), and Online Mendelian Inheritance in Man (OMIM) Database. The synergistic mechanisms of the SM and RP were evaluated by gene ontology (GO) enrichment analyses and Kyoto encyclopedia of genes and genomes (KEGG) path enrichment analyses. Result. A total of 61 active ingredients and 58 common targets were identified in this study. KEGG pathway enrichment analysis results showed that SM- and RP-regulated pathways were mainly inflammatory processes, immunosuppression, and cardiovascular systems. The component-target-pathway network indicated that SM and RP exert a synergistic mechanism for CCVDs through PTGS2 target in PI3k-Akt, TNF, and Jak-STAT signaling pathways. Conclusion. In summary, this study clarified the synergistic mechanisms of SM and RP, which can provide a better understanding of effect in the treatment of CCVDs.

scholarly journals A Systems Pharmacology Approach for Identifying the Multiple Mechanisms of Action for the Rougui-Fuzi Herb Pair in the Treatment of Cardiocerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chun Li ◽  
Xia Du ◽  
Yang Liu ◽  
Qi-Qi Liu ◽  
Wen Bing Zhi ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Chinese Herbs ◽  
Pathway Enrichment Analysis ◽  
High Morbidity ◽  
Active Ingredients ◽  
Active Compounds ◽  
System Pharmacology

Cardiocerebral vascular diseases (CCVDs) are the main reasons for high morbidity and mortality all over the world, including atherosclerosis, hypertension, myocardial infarction, stroke, and so on. Chinese herbs pair of the Cinnamomum cassia Presl (Chinese name, rougui) and the Aconitum carmichaelii Debx (Chinese name, fuzi) can be effective in CCVDs, which is recorded in the ancient classic book Shennong Bencao Jing, Mingyibielu and Thousand Golden Prescriptions. However, the active ingredients and the molecular mechanisms of rougui-fuzi in treatment of CCVDs are still unclear. This study was designed to apply a system pharmacology approach to reveal the molecular mechanisms of the rougui-fuzi anti-CCVDs. The 163 candidate compounds were retrieved from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). And 84 potential active compounds and the corresponding 42 targets were obtained from systematic model. The underlying mechanisms of the therapeutic effect for rougui-fuzi were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, component-target-disease (C-T-D) and target-pathway (T-P) networks were constructed to further dissect the core pathways, potential targets, and active compounds in treatment of CCVDs for rougui-fuzi. We also constituted protein-protein in interaction (PPI) network by the reflect target protein of the crucial pathways against CCVDs. As a result, 21 key compounds, 8 key targets, and 3 key pathways were obtained for rougui-fuzi. Afterwards, molecular docking was performed to validate the reliability of the interactions between some compounds and their corresponding targets. Finally, UPLC-Q-Exactive-MSE and GC-MS/MS were analyzed to detect the active ingredients of rougui-fuzi. Our results may provide a new approach to clarify the molecular mechanisms of Chinese herb pair in treatment with CCVDs at a systematic level.

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 Identification of the Active Constituents and Significant Pathways of Cangfu Daotan Decoction for the Treatment of PCOS Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Wenting Xu ◽  
Mengyu Tang ◽  
Jiahui Wang ◽  
Lihong Wang
Keyword(s):  
Clinical Symptoms ◽  
Polycystic Ovary ◽  
Endocrine Resistance ◽  
Enrichment Analysis ◽  
Signalling Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Significant Pathway

Background. Polycystic ovary syndrome (PCOS) is the most common female endocrine disease. Cangfu Daotan Decoction (CDD) can effectively relieve the clinical symptoms of PCOS patients. Methods. To explore the active ingredients and related pathways of CDD for treating PCOS, a network pharmacology-based analysis was carried out. The active ingredients of CDD and their potential targets were obtained from the TCM system pharmacology analysis platform. The obtained PCOS-related genes from OMIM and GeneCards were imported to establish protein-protein interaction networks in STRING. Finally, GO analysis and significant pathway analysis were conducted with the RStudio (Bioconductor) database. Results. A total of 111 active compounds were obtained from 1433 ingredients present in the CDD, related to 118 protein targets. In addition, 736 genes were found to be closely related to PCOS, of which 44 overlapped with CDD and were thus considered therapeutically relevant. Pathway enrichment analysis identified the AGE-RAGE signalling pathway in diabetic complications, endocrine resistance, the IL-17 signalling pathway, the prolactin signalling pathway, and the HIF-1 signalling pathway. Moreover, PI3K-Akt, insulin resistance, Toll-like receptor, MAPK, and AGE-RAGE were related to PCOS and treatment. Conclusions. CDD can effectively improve the symptoms of PCOS, and our network pharmacological analysis lays the foundation for future clinical research.

Pharmacological mechanism of Xiaoyao San in the treatment of polycystic ovary syndrome based on network pharmacology

2020 ◽  
Author(s):  
Chunyu Zhu ◽  
Yajun Hu ◽  
Wangdong Zheng ◽  
Yanyan Zhang ◽  
Yiting Li ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Drug Targets ◽  
Polycystic Ovary ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Ovary Syndrome ◽  
Pharmacological Mechanism ◽  
R Project

Abstract Background : Xiaoyao San(XYS) has been widely used in the treatment of polycystic ovary syndrome(PCOS), but its mechanism is not clear. The purpose of this study is to elucidate the mechanism of XYS in the treatment of PCOS from the aspects of active components, targets and pathways. The purpose of the study is to explore the molecular mechanism of XYS in the treatment of PCOS. Methods : TCMSP database, UniProt and Perl were used to screen and collect the active components and targets of XYS. The genes related to PCOS were searched in GeneCards database. Collect the related targets of PCOS and XYS, use STRING database and Cytoscape software to process the data visually and analyze topology, and screen the key components and targets in the network. The key targets were enriched by R Project to predict the mechanism of XYS in the treatment of PCOS. Results : 68 active components and 96 drug targets in XYS were screened out. 3648 PCOS related disease targets were collected. 66 targets of XYS for PCOS treatment were obtained after analysis. 21 key targets of NCOA2, PGR, PTGS1, PPARG and AR were constructed after topology analysis. 63 biological functions and 111 biological pathways were obtained after gene ontology(GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) Pathway enrichment analysis. Conclusions : XYS has the characteristics of multi-component, multi-target and multi-path. This study discussed the active components, targets and potential mechanism of XYS in the treatment of PCOS, which provided a new direction for further study of the mechanism of XYS in the treatment of PCOS, and provides more ideas for clinical treatment of PCOS.

scholarly journals Network Pharmacology Analysis on the Mechanism of Huangqi Sijunzi Decoction in Treating Cancer-Related Fatigue

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yixin Cui ◽  
Haiming Wang ◽  
Decai Wang ◽  
Jiwei Mi ◽  
Gege Chen ◽  
...  
Keyword(s):  
Topological Analysis ◽  
Enrichment Analysis ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Cancer Related Fatigue ◽  
Tumor Gene Expression

Objective. This study aimed to determine the active ingredients of Huangqi Sijunzi Decoction (HQSJZD) and the targets in treating cancer-related fatigue (CRF) so as to investigate the treatment mechanism of HQSJZD for CRF. Methods. This study adopted the method of network pharmacology. The active ingredients and targets of HQSJZD were retrieved, and the targets of HQSJZD in treating CRF were obtained using a Venn diagram. Next, a protein-protein interaction (PPI) network was constructed using the String database. The core targets of HQSJZD in treating CRF were identified through topological analysis, and functional annotation analysis and pathway enrichment analysis were carried out. Subsequently, a compound-disease-target regulatory network was constructed using Cystoscape 3.8.0 software. Results. A total of 250 targets of HQSJZD ingredients, 1447 CRF-related genes, and 144 common targets were obtained. Through topological analysis, 61 core targets were screened. Bioinformatics annotation of these genes identified 2366 gene ontology (GO) terms and 172 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Conclusion. The active ingredients in HQSJZD, that is, quercetin, luteolin, kaempferol, and naringenin, may act on AKT1, IL-6, VEGFA, MAPK3, CASP3, JUN, and EGFR to regulate the PI3K-Akt, TNF, and IL-17 signaling pathways, thereby suppressing inflammatory response, tumor gene expression, and tumor angiogenesis to treat CRF. This study investigated the pharmacological basis and mechanism of HQSJZD in the treatment of CRF using systematic pharmacology, which provides an important reference for further elucidation of the anti-CRF mechanism and clinical applications of HQSJZD, and also provides a method protocol for similar studies in the future.

scholarly journals Network pharmacology-based active compounds and pharmacological mechanisms of ginseng for depression in post-COVID-19

2020 ◽  
Author(s):  
Na Wang ◽  
Xianlei Wang ◽  
Mengjiao He ◽  
Wenxiu Zheng ◽  
Xiaoqing Cai ◽  
...  
Keyword(s):  
Immune Regulation ◽  
Enrichment Analysis ◽  
Sudden Onset ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Life Threatening Illness ◽  
Novel Coronavirus

Abstract Introduction: The novel coronavirus disease 2019 (COVID-19) is in the midst of worldwide panic. Sudden onset of an immediate life-threatening illness, quarantine and unemployment caused by epidemic are all contributors to depression. Ginseng has been reported to be an effective and safe clinical treatment on both immune-regulation and anti-depression. However, the mechanism of its anti-depression effect has not been fully characterized. In order to provide theoretical guidance for further clinical application in post-pandemic, we investigated active compounds and pharmacological mechanisms of ginseng to exert anti-depressant activity using network pharmacology, and discussed the active ingredients with immune-regulation and anti-depression.Methods: Information on compounds in ginseng was obtained from public databases, and genes related to depression were gathered using the GeneCards database. Networks of ginseng-associated targets and depression-related genes were constructed through STRING database. Potential targets and pathway enrichment analysis related to the therapeutic efficacy of ginseng for depression were identified using Cytoscape and Database for Annotation, Visualization and Integrated Discovery (DAVID). Results: Network pharmacological analysis of ginseng in treatment of depression identified 16 active ingredients, 47 potential targets, 32 GO terms, and 8 target gene-regulated major pathways. Among them, kaempferol, beta-sitosterol, stigmasterol, fumarine and frutinone A are bioactive compounds and key chemicals. Core genes in PPI network were AKT1, CASP3, NOS3, TNF, and PPARG. Enrichment results revealed that ginseng could regulate multiple aspects of depression through neuroactive ligand-receptor interaction, HIF-1 signaling pathway, and Serotonergic synapse. More importantly, we found that frutinone A and kaempferol are key ingredients in ginseng with dual activities of immune-regulation and anti-depression. Conclusions: We discovered that the therapeutic activities of ginseng for depression mainly involve neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response. Pharmacological network analysis can help to explain the potential effects of ginseng for treating depression, indicating that ginseng is a preferable herb clinically for immune-regulation and anti-depression in post-pandemic.

scholarly journals Investigation on the Mechanism of Qubi Formula in Treating Psoriasis Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Lin Zhou ◽  
Lingyun Zhang ◽  
Disheng Tao
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Cellular Response ◽  
Nuclear Translocation ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Core Network ◽  
Active Ingredients ◽  
Pharmacologically Active

Objective. To elucidate the pharmacological mechanisms of Qubi Formula (QBF), a traditional Chinese medicine (TCM) formula which has been demonstrated as an effective therapy for psoriasis in China. Methods. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, BATMAN-TCM database, and literature search were used to excavate the pharmacologically active ingredients of QBF and to predict the potential targets. Psoriasis-related targets were obtained from Therapeutic Target Database (TTD), DrugBank database (DBD), MalaCards database, and DisGeNET database. Then, we established the network concerning the interactions of potential targets of QBF with well-known psoriasis-related targets by using protein-protein interaction (PPI) data in String database. Afterwards, topological parameters (including DNMC, Degree, Closeness, and Betweenness) were calculated to excavate the core targets of Qubi Formula in treating psoriasis (main targets in the PPI network). Cytoscape was used to construct the ingredients-targets core network for Qubi Formula in treating psoriasis, and ClueGO was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets. Results. The ingredient-target-disease core network of QBF in treating psoriasis was screened to contain 175 active ingredients, which corresponded to 27 core targets. Additionally, enrichment analysis suggested that targets of QBF in treating psoriasis were mainly clustered into multiple biological processes (associated with nuclear translocation of proteins, cellular response to multiple stimuli (immunoinflammatory factors, oxidative stress, and nutrient substance), lymphocyte activation, regulation of cyclase activity, cell-cell adhesion, and cell death) and related pathways (VEGF, JAK-STAT, TLRs, NF-κB, and lymphocyte differentiation-related pathways), indicating the underlying mechanisms of QBF on psoriasis. Conclusion. In this work, we have successfully illuminated that Qubi Formula could relieve a wide variety of pathological factors (such as inflammatory infiltration and abnormal angiogenesis) of psoriasis in a “multicompound, multitarget, and multipathway” manner by using network pharmacology. Moreover, our present outcomes might shed light on the further clinical application of QBF on psoriasis treatment.

scholarly journals Identifying Synergistic Mechanisms of Multiple Ingredients in Shuangbai Tablets against Proteinuria by Virtual Screening and a Network Pharmacology Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiaoqin Ma ◽  
Meixiang Yu ◽  
Chenxia Hao ◽  
Wanhua Yang
Keyword(s):  
Molecular Docking ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Human Phenotype ◽  
Herbal Mixture ◽  
Relationship Of

Shuangbai Tablets (SBT), a traditional herbal mixture, has shown substantial clinical efficacy. However, a systematic mechanism of its active ingredients and pharmacological mechanisms of action against proteinuria continues being lacking. A network pharmacology approach was effectual in discovering the relationship of multiple ingredients and targets of the herbal mixture. This study aimed to identify key targets, major active ingredients, and pathways of SBT against proteinuria by network pharmacology approach combined with thin layer chromatography (TLC). Human phenotype (HP) disease analysis, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and molecular docking were used in this study. To this end, a total of 48 candidate targets of 118 active ingredients of SBT were identified. Network analysis showed PTGS2, ESR1, and NOS2 to be the three key targets, and beta-sitosterol, quercetin, and berberine were the three major active ingredients; among them one of the major active ingredients, quercetin, was discriminated by TLC. These results of the functional enrichment analysis indicated that the most relevant disease including these 48 candidate proteins is proteinuria, SBT treated proteinuria by sympathetically regulating multiple biological pathways, such as the HIF-1, RAS, AGE-RAGE, and VEGF signaling pathways. Additionally, molecular docking validation suggested that major active ingredients of SBT were capable of binding to HIF-1A and VEGFA of the main pathways. Consequently, key targets, major active ingredients, and pathways based on data analysis of SBT against proteinuria were systematically identified confirming its utility and providing a new drug against proteinuria.

scholarly journals Exploring the Mechanisms Underlying the Therapeutic Effect of Salvia Miltiorrhiza Against Diabetic Nephropathy Using Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Li-Li Zhang ◽  
Lin Han ◽  
Xin-Miao Wang ◽  
Yu Wei ◽  
Jing-Hui Zheng ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Therapeutic Effect ◽  
Molecular Mechanisms ◽  
Function Analysis ◽  
Salvia Miltiorrhiza ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Active Ingredients

Abstract BackgroundThe mechanisms underlying the therapeutic effect of Salvia Miltiorrhiza (SM) against diabetic nephropathy (DN) using systematic network pharmacology and molecular docking methods were examined.MethodsTCMSP database was used to screen the active ingredients of SM. Gene targets were obtained using Swiss Target Prediction and TCMSP databases. Related targets of DN were retrieved from the Genecards and DisGeNET databases. Next, a PPI network was constructed using the common targets of SM-DN in the STRING database. The Metascape platform was used for GO function analysis and Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for mapping the network. ResultsSixty-six active ingredients and 189 targets were screened from SM. Among them, 64 targets overlapped with DN targets. The PPI network diagram revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the top 10 relevant targets. GO and KEGG analyses mainly focused on advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that the potential target genes closely related to DN, including TNF, NOS2, and AKT1, were more stable in combination with salvianolic acid B, and their stability was better than that of tanshinone IIA.ConclusionThis study reveals the active components and potential molecular mechanisms involved in the therapeutic effect of SM against DN and provides a reference for the wide application of SM in clinically managing DN.

scholarly journals Utilizing Network Pharmacology to Explore the Possible Mechanism of Coptidis Rhizoma in Kawasaki Disease

2020 ◽  
Author(s):  
Xue Fan ◽  
Xin Guo ◽  
Ying Li ◽  
Mingguo Xu
Keyword(s):  
Kawasaki Disease ◽  
Signaling Pathway ◽  
Drug Targets ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Control Group ◽  
Pathway Enrichment Analysis ◽  
Routine Treatment ◽  
Coptidis Rhizoma

Abstract Background: Kawasaki disease (KD) is an acute self-limiting systemic vasculitis. In study, a randomized controlled trial regarding berberine (main component of Coptidis Rhizoma) function in treating KD was carried out and possible pharmacological mechanisms of Coptidis Rhizoma (CR) on KD therapy were investigated using an integrated network pharmacology approach. Methods: A total of 58 children with KD, younger than 5 years old, were enrolled in the study from October 2018 to May 2019. The patients were randomly divided into control group and BBR treatment group. The therapeutic indicators of the 2 groups before and after treatments were compared. Then, compounds and drug targets of CR from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the SWISS database, the SEA database and the STITCH database were collected, and targeted KD genes were retrieved from the DisGeNET databases, the DrugBank databases and the GeneCards databases. The network pharmacology approach involved network construction, target prediction, and module analysis. KEGG pathway and GO enrichment analysis were performed to investigate the molecular mechanisms and pathways related to CR for KD treatments. Results: The berberine group was able to reduce the values of CRP, NLR and PLR significantly. Also, the effect of berberine improved the resistance rate of intravenous injection of gamma globulin significantly. In total, 9 compounds and 369 relative drug targets were collected from TCMSP, SWISS, SEA and STITCH database and 624 KD target genes were collected in DisGeNET, DrugBank and GeneCards database. The network analysis revealed that 41 targets might be the therapeutic targets of CR on KD, among which ATK1, RELA, SRC, CASP3 and MTOR ranked in top 5. Gene ontology enrichment analysis revealed that the reaction to bacteria-derived molecules and to lipopolysaccharide and the apoptosis process were the key biological procedures for CR treating KD. The KEGG pathway enrichment analysis pointed out that the four signaling pathways closely related to CR treating KD including age-rage signaling pathway, fluid shear stress and atherosclerosis, TNF signaling pathway and Toll-like receptor signaling pathway in diabetic complications. Conclusions: we concluded that the introduction of routine treatment combined with berberine in treating KD has advantages than routine treatment and can be considered as a preferred approach in KD. Network pharmacology showed that CR exerted the effect of prevention KD by regulating multi-targets and multi-components.

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