Network Pharmacology Dissection of Multi-scale Mechanisms of Action of Tu-Xian Mixture for the Treatment of Diabetic Cognitive Impairment

Abstract Background Traditional Chinese medicine (TCM) has long been used in the treatment of diabetic cognitive impairment (DCI), and Tu-Xian mixture is one of the prescriptions. This study used a network pharmacology method to predict the active ingredients, potential targets and pathways of Tu-Xian mixture in the treatment of DCI.Methods The potential active ingredients of Tu-xian mixture were obtained by querying databases such as TCMSP, drug targets were screened through Pharmmapper, ETCM, and UniProt databases, and disease target protein groups were collected using TTD, OMIM, and CTD databases. Therapeutic targets were obtained by comparative analysis. Then use WebGestalt to complete GO enrichment analysis and KEGG pathway analysis.Results A total of 51 active ingredients and 619 potential targets were obtained, among which there were 33 key targets for diabetes and 18 key targets for cognitive impairment. After GO analysis and KEGG pathway analysis, steroid hormone biosynthesis and γ-aminobutyric acid signaling pathway may be the important metabolic pathways for Tu-Xian mixture to perform therapeutic effects.Conclusions This work promoted the comprehension of Tu-Xian mixture in the treatment of DCI, and further experimental verification of the prediction results was still needed to support its clinical application.

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Network Pharmacology Analysis of the active components and anticancer targets of Rhubarb

10.1101/2021.01.28.428583 ◽

2021 ◽

Author(s):

Hu Junrui ◽

Duan Yongqiang ◽

Cui Gongning ◽

Luo Qiang ◽

Xi Shanshan ◽

...

Keyword(s):

Pathway Analysis ◽

Drug Targets ◽

Target Genes ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Active Components ◽

Active Compounds ◽

Cellular Targets ◽

Kegg Pathway Analysis

AbstractTo investigate the mechanisms and active components governing the anticancer activity of rhubarb.The TCMSP database was screened to identify the active components of rhubarb and Swiss target predictions were generated to predict their cellular targets. TTD and OMIM databases were used to predict tumor-related target genes. "Cytoscape" was used to construct drug targets. PPI network analysis, GO enrichment analysis and KEGG pathway analysis of the key targets were investigated using String and David databases. A total of 33 components and 116 corresponding targets were screened. Amongst them, the key active compounds in rhubarb included emodin, aloe emodin, β-sitosterol, emodin methyl ether and rhein, which were predicted to target TP53, AKT1, STAT3, PIK3CA, HRAS, and VEGFA. GO analysis revealed that the cellular targets clustered into 159 biological processes, including those involved in cellular composition (n=24) and molecular functions (n=42, P<0.01). KEGG pathway analysis revealed 85 (P < 0.01) pathways related to cancer. The active compounds in rhubarb target TP53, AKT1 and PIK3CA. Rhubarb therefore regulates cancer development through an array of biological pathways.

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Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190717124507 ◽

2019 ◽

Vol 22 (6) ◽

pp. 411-420 ◽

Cited By ~ 5

Author(s):

Xian-Jun Wu ◽

Xin-Bin Zhou ◽

Chen Chen ◽

Wei Mao

Keyword(s):

Cardiovascular Disease ◽

Cardiovascular Diseases ◽

Signaling Pathway ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Therapeutic Effects ◽

Pathway Enrichment ◽

Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

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Explore the mechanism of Shengma-Gegen drug pair on hepatitis B virus based on network pharmacology

10.21203/rs.3.rs-59583/v1 ◽

2020 ◽

Author(s):

Guozhe Zhang ◽

Chunmiao Chen ◽

Yiyu Qin ◽

Jianwei Ji

Keyword(s):

Hepatitis B Virus ◽

Hepatitis B ◽

Pathway Analysis ◽

Cellular Response ◽

Kegg Pathway ◽

Drug Pair ◽

Kegg Pathway Analysis ◽

Go Enrichment ◽

B Virus ◽

Ethanol Extracts

Abstract Background Sheng-Ma-Ge-Gen-Tang (SMGGT; 升麻葛根汤) is a famous prescription of traditional Chinese medicine used against measles of children for many hundreds of years. And its anti-hepatitis B virus (HBV) activity has been justified in clinical, however, the function substances and the mechanisms have not been studied yet. Methods The latent active compounds of Cimicifugae Rhizoma (Shengma)-Radix Puerariae (Gegen) drug pair were searched, and excavated their related targets. Then seek the targets of HBV through three network databases. The drug-disease targets of protein-protein interaction (PPI) data was carried out. The drug-disease targets were enriched by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subsequently, anti-HepG2.2.15 cytotoxicity and anti-HBV experiments were performed on the aqueous and ethanol extracts of Shengma-Gegen in vitro to test and verify their anti-HBV activities. Results GO enrichment indicated biological processes (cellular response to lipid, cellular response to organic cyclic compound, etc.), cellular components (vesicle lumen, cytoplasmic vesicle lumen, etc.) and molecular function (kinase binding, steroid binding, etc.). Many cancer-related pathways were enriched in KEGG pathway analysis. Also got some virus and bacteria diseases. A KEGG-targets network showed that RAF1, CCND1, BCL2, and EGFR might be the core targets. Cytotoxicity of Shengma and Gegen to HepG2.2.15 are in proportion to their concentrations. Shengma and Gegen aqueous and ethanol extracts exhibited a curtain extant anti-HBV-DNA activity. Conclusions Shengma-Gegen showed not only anti-HBV activity but also anti-tumor and anti-viral activities, which need to be tested in the future.

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The Mechanism of Jinqi Jiangtang Tablet in Treatment of Type 2 Diabetes Mellitus Based on Network Pharmacology

10.21203/rs.3.rs-59586/v1 ◽

2020 ◽

Author(s):

Mingjun Yang ◽

Boni Song ◽

Zhitong Bing ◽

Juxiang Liu ◽

Rui Li ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Drug Targets ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Active Compounds ◽

Online Tool

Abstract Background: Type 2 Diabetes Mellitus(T2DM) is an endocrine disease that caused mainly by insulin resistance (IR) and β cell dysfunction. The incidence of T2DM is quite high in the worldwide. To explore the molecular mechanism of Jinqi Jiangtang Tablet(JJT) in treating of T2DM based on Network Pharmacology. Methods: The active compounds, targets of three Traditional Chinese medicines in JJT were obtained by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform（TCMSP） database and Uniprot database; The targets of T2DM were screened through the Drugbank database; The compound-target network was constructed via the Cytoscape 3.7.2 software and used the built-in Network analyzer to analyze and select the key active compounds; The overlapping targets of drug and disease targets were gained by the VENNY online tool and the targets were built by STRING website to select the key genes; Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed on the potential targets using DAVID6.8 online tool to study the mechanism of overlapping targets. Via Systems Dock platform to validate the interaction between compound and targets Results: Twenty-five active compounds of JJT were screened, 101 drug targets, 142 disease targets and twenty-one overlapping targets. GO enrichment analysis showed that the biological processes (BP)mainly included the blood circulation ,etc. Cell composition(CC) mainly affected the integral component of plasma membrane, etc. Molecular functions(MF) mainly involved alpha-adrenergic receptor activity, etc. KEGG pathway analysis showed that there were twelve pathways related to T2DM, among which PPAR signaling pathway was related to T2DM mostly. RXRA is one of key targets of JJT and berberine performed well. Conclusions: This study revealed the mechanism of JJT in treatment of T2DM preliminarily and supplied a further foundation for studying its mechanism.

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Mechanisms of Berberine for the Treatment of Atherosclerosis Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/3568756 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Xuejiao Xie ◽

Xingyu Ma ◽

Siyu Zeng ◽

Wansi Tang ◽

Liucheng Xiao ◽

...

Keyword(s):

Signaling Pathway ◽

Pathway Analysis ◽

Kegg Pathway ◽

Functional Enrichment ◽

Network Pharmacology ◽

Foam Cell Formation ◽

Ppi Network ◽

The Core ◽

Ppi Networks ◽

Kegg Pathway Analysis

Atherosclerosis is a common metabolic disease characterized by lipid metabolic disorder. The processes of atherosclerosis include endothelial dysfunction, new endothelial layer formation, lipid sediment, foam cell formation, plaque formation, and plaque burst. Owing to the adverse effects of first-line medications, it is urgent to discover new medications to deal with atherosclerosis. Berberine is one of the most promising natural products derived from traditional Chinese medicine. However, the panoramic mechanism of berberine against atherosclerosis has not been discovered clearly. In this study, we used network pharmacology to investigate the interaction between berberine and atherosclerosis. We identified potential targets related to berberine and atherosclerosis from several databases. A total of 31 and 331 putative targets for berberine and atherosclerosis were identified, respectively. Then, we constructed berberine and atherosclerosis targets with PPI data. Berberine targets network with PPI data had 3204 nodes and 79437 edges. Atherosclerosis targets network with PPI data had 5451 nodes and 130891 edges. Furthermore, we merged the two PPI networks and obtained the core PPI network from the merged PPI network. The core PPI network had 132 nodes and 3339 edges. At last, we performed functional enrichment analyses including GO and KEGG pathway analysis in David database. GO analysis indicated that the biological processes were correlated with G1/S transition of mitotic cells cycle. KEGG pathway analysis found that the pathways directly associated with berberine against atherosclerosis were cell cycle, ubiquitin mediated proteolysis, MAPK signaling pathway, and PI3K-Akt signaling pathway. After combining the results in context with the available treatments for atherosclerosis, we considered that berberine inhibited inflammation and cell proliferation in the treatment of atherosclerosis. Our study provided a valid theoretical foundation for future research.

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

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/6937186 ◽

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.

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Exploring the Potential Mechanism of Xiaokui Jiedu Decoction for Ulcerative Colitis Based on Network Pharmacology and Molecular Docking

Journal of Healthcare Engineering ◽

10.1155/2021/1536337 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Bin Wang ◽

Yang Liu ◽

Jianhui Sun ◽

Nailin Zhang ◽

Xiaojia Zheng ◽

...

Keyword(s):

Ulcerative Colitis ◽

Molecular Docking ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Potential Mechanism ◽

Related Gene ◽

Active Ingredients ◽

Colon Cells ◽

Hub Gene

Introduction. Network pharmacology is in line with the holistic characteristics of TCM and can be used to elucidate the complex network of interactions between disease-specific genes and compounds in TCM herbal medicines. Here, we investigate the pharmacological mechanism of Xiaokui Jiedu decoction (XJD) for the treatment of ulcerative colitis (UC). Methods. The Computational Systems Biology Laboratory Platform (TCMSP) database was searched and screened for the active ingredients of all drugs in XJD. The Uniport database was used to retrieve possible gene targets for the therapeutic effects of XJD. GeneCards, PharmGKB, TTD, and OMIM databases were used to retrieve XJD-related gene targets. A herb-compound-protein network and a protein-protein interaction (PPI) network were constructed, and hub genes were screened for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to validate the interrelationship between disease target proteins and active drug components. Results. A total of 135 XJD potential action targets, 5097 UC-related gene targets, and 103 XJD-UC intersection gene targets were screened. The hub gene targets of XJD that exert therapeutic effects on UC are RB1, MAPK1, TP53, JUN, NR3C1, MAPK3, and ESR1. GO enrichment analysis showed 741 biofunctional enrichments, and KEGG enrichment analysis showed 124 related pathway enrichments. Molecular docking showed that the active components of XJD (β-sitosterol, kaempferol, formononetin, quercetin, and luteolin) showed good binding activities to five of the six hub gene targets. Discussion. The active ingredients of XJD (β-sitosterol, kaempferol, formononetin, quercetin, and luteolin) may regulate the inflammatory and oxidative stress-related pathways of colon cells during the course of UC by binding to the hub gene targets. This may be a potential mechanism of XJD in the treatment of UC.

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Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients

Briefings in Bioinformatics ◽

10.1093/bib/bbab373 ◽

2021 ◽

Author(s):

Hong Wang ◽

Jingqing Zhang ◽

Zhigang Lu ◽

Weina Dai ◽

Chuanjiang Ma ◽

...

Keyword(s):

Drug Targets ◽

Drug Repurposing ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Protein Protein Interaction ◽

Disease Module ◽

Approved Drugs ◽

Data Driven Modeling ◽

The Relationship

Abstract After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein–protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

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

10.21203/rs.3.rs-124429/v1 ◽

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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Exploration of the Mechanism and Active Targets of Chinese Herbal Formula, JTTZ, for the Treatment of Type 2 Diabetes with Obesity and Hyperlipidemia Based on Network Pharmacology

10.21203/rs.3.rs-147873/v1 ◽

2021 ◽

Author(s):

Haiyu Zhang ◽

Xuedong An ◽

De Jin ◽

Jiaxing Tian ◽

Wenke Liu ◽

...

Keyword(s):

Inflammatory Response ◽

Signaling Pathway ◽

Pathway Analysis ◽

Kegg Pathway ◽

Therapeutic Targets ◽

Mapk Signaling ◽

Network Pharmacology ◽

Bile Acid Metabolism ◽

Ppi Networks ◽

Kegg Pathway Analysis

Abstract BackgroundPrevious studies have indicated that the JTTZ formula exhibits clinical benefit in T2D with obesity and hyperlipidemia such as lowering blood glucose, blood lipids, weight, and ameliorating symptoms as well as regulating islet function. However, their mechanism of action remains unclear. T2D with obesity and hyperlipidemia is associated with a severely poor management duo to difficulty in achieving the clinical goals and lack of effective multi-targeted therapies. In this study, we explored its potential mechanisms and therapeutic targets by network pharmacology. MethodsThe active ingredients and targets of JTTZ were obtained in the TCMSP, TCMID, TCM Database@Taiwan, PubChem and Swiss Target Prediction. And the therapeutic targets were searched from TTD, DrugBank Database and DisGeNET. Then, topology analysis were used as secondary screens to identify key hubs of the network. Finally, the data was integrated by Cytoscape software to construct a common network module. PPI networks were visualized to identify the interaction of the candidate targets. GO and KEGG pathway analysis were implemented. Rerult: 110 active compounds and 166 candidate targets of JTTZ against T2D with obesity and hyperlipidemia were obtained to construct compound-targets network. And, the therapeutic targets AKT2, RELA, NFKB1 and GSK3B were identified. GO and KEGG pathway analysis indicated that the biological processes related to inflammatory response, insulin secretion, steroid and bile acid metabolism, and 13 pathways mainly including adipocytokine signaling pathway, cAMP signaling pathway and cGMP-PKG signaling pathway were enriched. ConclusionOur data established that JTTZ intervenes with adipose tissue dysfunction via regulating to the adipocytokine (leptin and adiponectin), AMPK signaling pathway, cAMP and cGMP-PKG signaling pathway, inhibits systematic inflammatory response by NF-κB and MAPK signaling pathway, and ameliorates insulin resistance through PI3K/AKT2 pathway, all of which could thus offer a promising therapeutic strategy. In addition, AKT2, RELA, NFKB1 and GSK3B were identified to be regarded as potential therapeutic targets as well.

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