scholarly journals Network Pharmacology and Metabolomics Studies on Antimigraine Mechanisms of Da Chuan Xiong Fang (DCXF)

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Shiyu Ma ◽  
Lin Zheng ◽  
Xiao Lin ◽  
Yi Feng ◽  
Ming Yang ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Brain Tissue ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Fatty Acid Transport ◽  
Hub Genes ◽  
Hydroxytryptamine Receptors ◽  
Protein Protein Interaction

Background. Da Chuan Xiong Fang (DCXF) is a traditional Chinese medicine (TCM) formula used to treat migraines. Previously, we uncovered partial mechanisms involved in the therapeutic actions of DCXF on migraines. Methods. In this study, we further elucidated its antimigraine mechanisms in vivo by using an integrated strategy coupling with network pharmacology and metabolomics techniques. Results. Network pharmacology identified 33 genes linked with both migraine and DCXF, most of which were 5-hydroxytryptamine receptors, dopamine, and peptide receptors. The results of GO and KEGG enrichment analysis showed that DCXF significantly regulated tyrosine metabolism, tryptophan metabolism, dopamine metabolic process, glucose transmembrane transport, lipid metabolism, and fatty acid transport. The results of metabolomics analysis found that the metabolism of tryptophan and tyrosine in the brain tissue and energy and lipid metabolism of rats tended towards normal and reached normal levels after administering DCXF. The metabolomics and network pharmacology approaches demonstrated similar antimigraine effects of DCXF on endogenous neurotransmitters and overall trends in serum and brain tissue. Using both approaches, 62 hub genes were identified from the protein-protein interaction (PPI) network of DCXF and gene-metabolite interaction network, with hub genes and different metabolites in serum and brain tissue. The hub genes of DCXF, which were mostly linked with inflammation, might affect mainly neurotransmitters in serum and brain tissue metabolisms. Conclusion. Network pharmacology and metabolomics study may help identify hub genes, metabolites, and possible pathways of disease and treatment. Additionally, two parts of the results were integrated to confirm each other. Their combination may help elucidate the relationship between hub genes and metabolites and provide the further understanding of TCM mechanisms.

scholarly journals A Network Pharmacology Approach to Investigating the Mechanism of Sophorae Flavescentis Radix for the Treatment of Lung Cancer

2020 ◽  
Author(s):  
Le Yu ◽  
Kangyao Yuan ◽  
Jian Zhang ◽  
Jingya Zhao ◽  
Shuchen Pei
Keyword(s):  
Lung Cancer ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Akt Signaling Pathway ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Human Cytomegalovirus Infection ◽  
Protein Protein Interaction Network

Abstract In this study, the bioactive components and predictive targets of Sophorae Flavescentis Radix were investigated by network pharmacology analysis, so as to further elucidate its potential biological mechanism in treating lung cancer. The targets corresponding to lung cancer were obtained by OMIM and Genecards. By intersecting with the targets of Sophorae Flavescentis Radix and lung cancer, the Sophorae Flavescentis Radix-lung cancer targets were obtained. Protein-protein interaction network was constructed by an online database STRING and hub genes were screened by Cytoscape 3.7.0 software. ClusterProfiler package was used to analyze Gene ontology (GO) and KEGG enrichment of the targets in R. A total of 45 bioactive components were screened from Sophorae Flavescentis Radix, corresponding to 482 Sophorae Flavescentis Radix targets and 25019 lung cancer targets. According to the GO and KEGG enrichment analysis, Sophorae Flavescentis Radix played a therapeutic role in treating lung cancer via proteoglycans lung cancer, human cytomegalovirus infection, microRNAs in cancer, PI3K-Akt signaling pathway, etc. Seven hub genes (IL6, CASP3, EGFR, VEGFA, MYC, CCND1 and ESR1) were screened by degree algorithm. In a word, the results of this study may provide novel insights into the mechanisms of Sophorae Flavescentis Radix in treatment of lung cancer.

scholarly journals Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098213
Author(s):  
Xiaodong Deng ◽  
Yuhua Liang ◽  
Jianmei Hu ◽  
Yuhui Yang
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Topological Parameters

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

scholarly journals Elucidating the Mechanisms of Action of Lianhua Qingwen decoction for the Treatment of COVID-19 via Systems Pharmacology Approaches

2021 ◽  
Author(s):  
Xiting Wang ◽  
Tao Lu
Keyword(s):  
Molecular Docking ◽  
Blood Circulation ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Detection Algorithm ◽  
Network Pharmacology ◽  
Systems Pharmacology ◽  
Protein Protein Interaction ◽  
Further Development ◽  
Protein Protein Interaction Network

Abstract Due to the severity of the COVID-19 epidemic, to identify a proper treatment for COVID-19 is of great significance. Traditional Chinese Medicine (TCM) has shown its great potential in the prevention and treatment of COVID-19. One of TCM decoction, Lianhua Qingwen decoction displayed promising treating efficacy. Nevertheless, the underlying molecular mechanism has not been explored for further development and treatment. Through systems pharmacology and network pharmacology approaches, we explored the potential mechanisms of Lianhua Qingwen treating COVID-19 and acting ingredients of Lianhua Qingwen decoction for COVID-19 treatment. Through this way, we generated an ingredients-targets database. We also used molecular docking to screen possible active ingredients. Also, we applied the protein-protein interaction network and detection algorithm to identify relevant protein groupings of Lianhua Qingwen. Totally, 605 ingredients and 1,089 targets were obtained. Molecular Docking analyses revealed that 35 components may be the promising acting ingredients, 7 of which were underlined according to the comprehensive analysis. Our enrichment analysis of the 7 highlighted ingredients showed relevant significant pathways that could be highly related to their potential mechanisms, e.g. oxidative stress response, inflammation, and blood circulation. In summary, this study suggests the promising mechanism of the Lianhua Qingwen decoction for COVID-19 treatment. Further experimental and clinical verifications are still needed.

scholarly journals A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Sha Di ◽  
Lin Han ◽  
Qing Wang ◽  
Xinkui Liu ◽  
Yingying Yang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Regulation Of Blood Pressure ◽  
Protein Protein Interaction Network

Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.

scholarly journals Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

2019 ◽  
Author(s):  
Yunze Liu ◽  
Xiaojie Sun ◽  
Aijun Qu
Keyword(s):  
Drosophila Melanogaster ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Neuronal Remodeling ◽  
Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

scholarly journals Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

2019 ◽  
Author(s):  
Yunze Liu ◽  
Xiaojie Sun ◽  
Aijun Qu
Keyword(s):  
Drosophila Melanogaster ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Neuronal Remodeling ◽  
Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

scholarly journals Network Pharmacology Study on the Pharmacological Mechanism of Cinobufotalin Injection against Lung Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yun Mao ◽  
Xi Peng ◽  
Peng Xue ◽  
Dianrong Lu ◽  
Linlu Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Therapeutic Targets ◽  
Target Prediction ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Protein Protein Interaction ◽  
Pharmacological Mechanism ◽  
Chinese Giant Salamander ◽  
Receptor Signaling Pathway

Cinobufotalin injection, extracted from the skin of Chinese giant salamander or black sable, has good clinical effect against lung cancer. However, owing to its complex composition, the pharmacological mechanism of cinobufotalin injection has not been fully clarified. This study aimed to explore the mechanism of action of cinobufotalin injection against lung cancer using network pharmacology and bioinformatics. Compounds of cinobufotalin injection were determined by literature retrieval, and potential therapeutic targets of cinobufotalin injection were screened from Swiss Target Prediction and STITCH databases. Lung-cancer-related genes were summarized from GeneCards, OMIM, and DrugBank databases. The pharmacological mechanism of cinobufotalin injection against lung cancer was determined by enrichment analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction network was constructed. We identified 23 compounds and 506 potential therapeutic targets of cinobufotalin injection, as well as 70 genes as potential therapeutic targets of cinobufotalin injection in lung cancer by molecular docking. The antilung cancer effect of cinobufotalin injection was shown to involve cell cycle, cell proliferation, antiangiogenesis effect, and immune inflammation pathways, such as PI3K-Akt, VEGF, and the Toll-like receptor signaling pathway. In network analysis, the hub targets of cinobufotalin injection against lung cancer were identified as VEGFA, EGFR, CCND1, CASP3, and AKT1. A network diagram of “drug-compounds-target-pathway” was constructed through network pharmacology to elucidate the pharmacological mechanism of the antilung cancer effect of cinobufotalin injection, which is conducive to guiding clinical medication.

Virtual Screening of Potential Anti-fatigue Mechanism of Polygonati Rhizoma Based on Network Pharmacology

2020 ◽  
Vol 22 (9) ◽  
pp. 612-624 ◽  
Author(s):  
Ze-Feng Wang ◽  
Ye-Qing Hu ◽  
Qi-Guo Wu ◽  
Rui Zhang
Keyword(s):  
Virtual Screening ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Vital Role ◽  
Network Pharmacology ◽  
Pathway Network ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Protein Protein Interaction Network ◽  
Fatigue Mechanism

Background and Objective: A large number of people are facing the danger of fatigue due to the fast-paced lifestyle. Fatigue is common in some diseases, such as cancer. The mechanism of fatigue is not definite. Traditional Chinese medicine is often used for fatigue, but the potential mechanism of Polygonati Rhizoma (PR) is still not clear. This study attempts to explore the potential anti-fatigue mechanism of Polygonati Rhizoma through virtual screening based on network pharmacology. Methods: The candidate compounds of PR and the known targets of fatigue are obtained from multiple professional databases. PharmMapper Server is designed to identify potential targets for the candidate compounds. We developed a Herbal medicine-Compound-Disease-Target network and analyzed the interactions. Protein-protein interaction network is developed through the Cytoscape software and analyzed by topological methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment are carried out by DAVID Database. Finally, we develop Compound-Target-Pathway network to illustrate the anti-fatigue mechanism of PR. Results: This approach identified 12 active compounds and 156 candidate targets of PR. The top 10 annotation terms for GO and KEGG were obtained by enrichment analysis with 35 key targets. The interaction between E2F1 and PI3K-AKT plays a vital role in the anti-fatigue effect of PR due to this study. Conclusions: This study demonstrates that PR has multi-component, multi-target and multipathway effects.

Exploring Shared Pathogenesis of Alzheimer’s Disease and Type 2 Diabetes Mellitus via Co-expression Networks Analysis

2020 ◽  
Vol 17 (6) ◽  
pp. 566-575 ◽  
Author(s):  
Yukun Zhu ◽  
Xuelu Ding ◽  
Zhaoyuan She ◽  
Xue Bai ◽  
Ziyang Nie ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Background: Alzheimer’s Disease (AD) and Type 2 Diabetes Mellitus (T2DM) have an increased incidence in modern society. Although increasing evidence has supported the close linkage between these two disorders, the inter-relational mechanisms remain to be fully elucidated. Objective: The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and T2DM. Methods: We downloaded the microarray data of AD and T2DM from the Gene Expression Omnibus (GEO) database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis (WGCNA) to identify gene network modules related to AD and T2DM. Then, Gene Ontology (GO) and pathway enrichment analysis were performed on the common genes existing in the AD and T2DM related modules by clusterProfiler and DOSE package. Finally, we utilized the STRING database to construct the protein-protein interaction network and found out the hub genes in the network. Results: Our findings indicated that seven and four modules were the most significant with AD and T2DM, respectively. Functional enrichment analysis showed that AD and T2DM common genes were mainly enriched in signaling pathways such as circadian entrainment, phagosome, glutathione metabolism and synaptic vesicle cycle. Protein-protein interaction network construction identified 10 hub genes (CALM1, LRRK2, RBX1, SLC6A1, TXN, SNRPF, GJA1, VWF, LPL, AGT) in AD and T2DM shared genes. Conclusions: Our work identified common pathogenesis of AD and T2DM. These shared pathways might provide a novel idea for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosis and treatment of AD and T2DM.

Identification of IL-6 as a potential mediator of the myocardial fibrosis that occurs in response to surgery with cardiopulmonary bypass in children with Tetralogy of Fallot

2021 ◽  
pp. 1-7
Author(s):  
Hongtao Liu ◽  
Yun Zhang ◽  
Zhenhai Wu ◽  
Liangqing Zhang
Keyword(s):  
Heart Failure ◽  
Network Analysis ◽  
Myocardial Fibrosis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Gene Correlation ◽  
Cell Expression

Abstract Background: Tetralogy of Fallot is a common CHD. Studies have shown a close link between heart failure and myocardial fibrosis. Interleukin-6 has been suggested to be a post-independent factor of heart failure. This study aimed to explore the relationship between IL-6 and myocardial fibrosis during cardiopulmonary bypass. Material and Methods: We downloaded the expression profile dataset GSE132176 from Gene Expression Omnibus. After normalising the raw data, Gene Set Enrichment Analysis and differential gene expression analysis were performed using R. Further, a weighted gene correlation network analysis and a protein–protein interaction network analysis were used to identify HUB genes. Finally, we downloaded single-cell expression data for HUB genes using PanglaoDB. Results: There were 119 differentially expressed genes in right atrium tissues comparing the post-CPB group with the pre-CPB group. IL-6 was found to be significantly up-regulated in the post-CPB group. Six genes (JUN, FOS, ATF3, EGR1, IL-6, and PTGS2) were identified as HUB genes by a weighted gene correlation network analysis and a protein–protein interaction network analysis. Gene Set Enrichment Analysis showed that IL-6 affects the myocardium during CPB mainly through the JAK/STAT signalling pathway. Finally, we used PanglaoDB data to analyse the single-cell expression of the HUB genes. Conclusion: Our findings suggest that high expression of IL-6 and the activation of the JAK/STAT signalling pathway during CPB maybe the potential mechanism of myocardial fibrosis. We speculate that the high expression of IL-6 might be an important factor leading to heart failure after ToF surgery. We expect that these findings will provide a basis for the development of targeted drugs.

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