Investigation of the Mechanism of Shengmai Injection on Sepsis by Network Pharmacology Approaches
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ABSTRACT:
SUBMITTER: Lu J
PROVIDER: S-EPMC7422069 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Project description:At present, although the early treatment of sepsis is advocated, the treatment effect of sepsis is unsatisfactory, and the mortality rate remains high. Shenfu injection (SFI) has been used to treat sepsis with good clinical efficacy. Based on network pharmacology, this study adopted a new research strategy to identify the potential therapeutic targets and key active ingredients of SFI for sepsis from the perspective of the pathophysiology of sepsis. This analysis identified 28 active ingredients of SFI based on UHPLC-QQQ MS, including 18 ginsenosides and 10 aconite alkaloids. 59 targets were associated with the glycocalyx and sepsis pathways. Based on the number of targets related to the pathophysiological process of sepsis, we identified songorine, ginsenoside Rf, ginsenoside Re, and karacoline as the key active ingredients of SFI for the treatment of sepsis. According to the cluster analysis of MCODE and the validation on the GEO dataset, LGALS3, BCHE, AKT1, and IL2 were identified as the core targets. This study further explored the therapeutic mechanism and the key active ingredients of SFI in sepsis and provided candidate compounds for drug development.
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Project description:Reduning Injection (RDNI) is a traditional Chinese medicine formula indicated for the treatment of inflammatory diseases. However, the molecular mechanism of RDNI is unclear. The information of RDNI ingredients was collected from previous studies. Targets of them were obtained by data mining and molecular docking. The information of targets and related pathways was collected in UniProt and KEGG. Networks were constructed and analyzed by Cytoscape to identify key compounds, targets, and pathways. Data mining and molecular docking identified 11 compounds, 84 targets, and 201 pathways that are related to the anti-inflammatory activity of RDNI. Network analysis identified two key compounds (caffeic acid and ferulic acid), five key targets (Bcl-2, eNOS, PTGS2, PPARA, and MMPs), and four key pathways (estrogen signaling pathway, PI3K-AKT signaling pathway, cGMP-PKG signaling pathway, and calcium signaling pathway) which would play critical roles in the treatment of inflammatory diseases by RDNI. The cross-talks among pathways provided a deeper understanding of anti-inflammatory effect of RDNI. RDNI is capable of regulating multiple biological processes and treating inflammation at a systems level. Network pharmacology is a practical approach to explore the therapeutic mechanism of TCM for complex disease.
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Project description:BACKGROUND:Shenmai injection (SMI) has been used in the treatment of cardiovascular disease (CVD), such as heart failure, myocardial ischemia and coronary heart disease. It has been found to have efficacy on doxorubicin (DOX)-induced cardiomyopathy. The aims of this study were to explore the underlying molecular mechanisms of SMI treatment on CVD by using network pharmacology and its protective effect on DOX-induced cardiotoxicity by in vitro and in vivo experiment based on network pharmacology prediction. METHODS:Network pharmacology method was used to reveal the relationship between ingredient-target-disease and function-pathway of SMI on the treatment of CVD. Chemical ingredients of SMI were collected form TCMSP, BATMAN-TCM and HIT Database. Drugbank, DisGeNET and OMIM Database were used to obtain potential targets for CVD. Networks were visualized utilizing Cytoscape software, and the enrichment analysis was performed using IPA system. Finally, cardioprotective effects and predictive mechanism confirmation of SMI were investigated in H9c2 rat cardiomyocytes and DOX-injured C57BL/6 mice. RESULTS:An ingredient-target-disease & function-pathway network demonstrated that 28 ingredients derived from SMI modulated 132 common targets shared by SMI and CVD. The analysis of diseases & functions, top pathways and upstream regulators indicated that the cardioprotective effects of SMI might be associated with 28 potential ingredients, which regulated the 132 targets in cardiovascular disease through regulation of G protein-coupled receptor signaling. In DOX-injured H9c2 cardiomyocytes, SMI increased cardiomyocytes viability, prevented cell apoptosis and increased PI3K and p-Akt expression. This protective effect was markedly weakened by PI3K inhibitor LY294002. In DOX-treated mice, SMI treatment improved cardiac function, including enhancement of ejection fraction and fractional shortening. CONCLUSIONS:Collectively, the protective effects of SMI on DOX-induced cardiotoxicity are possibly related to the activation of the PI3K/Akt pathway, as the downstream of G protein-coupled receptor signaling pathway.
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Project description: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.
| S-EPMC7048923 | biostudies-literature
Project description:To explore the mechanism of Shengmai Yin (SMY) for coronary heart disease (CHD) by systemic pharmacology and chemoinformatics. Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), traditional Chinese medicine integrative database (TCMID) and the traditional Chinese medicine (TCM) Database@Taiwan were used to screen and predict the bioactive components of SMY. Pharmmapper were utilized to predict the potential targets of SMY, the TCMSP was utilized to obtain the known targets of SMY. The Genecards and OMIM database were utilized to collect CHD genes. Cytoscape was then used for network construction and analysis, and DAVID was used for Gene Ontology (GO) and pathway enrichment analysis. After that, animal experiments were then performed to further validate the results of systemic pharmacology and chemoinformatics. Three major networks were constructed: (1) CHD genes' protein-protein interaction (PPI) network; (2) SMY-CHD PPI network; (3) SMY known target-CHD PPI network. The other networks are minor networks generated by analyzing the three major networks. Experimental results showed that compared with the model group, the Shengmai injection (SMI) can reduce the myocardial injury score and the activities of serum aspartate aminoconvertase (AST), CK and lactate dehydrogenase (LDH) in rats (P<0.05), and reduce serum lipid peroxide (LPO) content and increase serum superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities in myocardial infarction rats (P<0.05). SMI can also decrease the expression of MMP-9 mRNA and increase that of TIMP-1 mRNA (P<0.01). SMY may regulate the signaling pathways (such as PPAR, FoxO, VEGF signaling), biological processes (such as angiogenesis, blood pressure formation, inflammatory response) and targets (such as AKT1, EGFR, MAPK1) so as to play a therapeutic role in CHD.
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Project description:MotivationDrug discovery investigations need to incorporate network pharmacology concepts while navigating the complex landscape of drug-target and target-target interactions. This task requires solutions that integrate high-quality biomedical data, combined with analytic and predictive workflows as well as efficient visualization. SmartGraph is an innovative platform that utilizes state-of-the-art technologies such as a Neo4j graph-database, Angular web framework, RxJS asynchronous event library and D3 visualization to accomplish these goals.ResultsThe SmartGraph framework integrates high quality bioactivity data and biological pathway information resulting in a knowledgebase comprised of 420,526 unique compound-target interactions defined between 271,098 unique compounds and 2018 targets. SmartGraph then performs bioactivity predictions based on the 63,783 Bemis-Murcko scaffolds extracted from these compounds. Through several use-cases, we illustrate the use of SmartGraph to generate hypotheses for elucidating mechanism-of-action, drug-repurposing and off-target prediction.Availabilityhttps://smartgraph.ncats.io/.
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Project description:ObjectiveTo 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.MethodsThe 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.ResultsThe 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.ConclusionIn 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.
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Project description:BackgroundThe Coronavirus Disease 2019 (COVID-19) outbreak in Wuhan, China, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Anisodamine hydrobromide injection (AHI), the main ingredient of which is anisodamine, is a listed drug for improving microcirculation in China. Anisodamine can improve the condition of patients with COVID-19.Materials and methodsProtein-protein interactions obtained from the String databases were used to construct the protein interaction network (PIN) of AHI using Cytoscape. The crucial targets of AHI PIN were screened by calculating three topological parameters. Gene ontology and pathway enrichment analyses were performed. The intersection between the AHI component proteins and angiotensin-converting enzyme 2 (ACE2) coexpression proteins was analyzed. We further investigated our predictions of crucial targets by performing molecular docking studies with anisodamine.ResultsThe PIN of AHI, including 172 nodes and 1454 interactions, was constructed. A total of 54 crucial targets were obtained based on topological feature calculations. The results of Gene Ontology showed that AHI could regulate cell death, cytokine-mediated signaling pathways, and immune system processes. KEGG disease pathways were mainly enriched in viral infections, cancer, and immune system diseases. Between AHI targets and ACE2 coexpression proteins, 26 common proteins were obtained. The results of molecular docking showed that anisodamine bound well to all the crucial targets.ConclusionThe network pharmacological strategy integrated molecular docking to explore the mechanism of action of AHI against COVID-19. It provides protein targets associated with COVID-19 that may be further tested as therapeutic targets of anisodamine.
| S-EPMC7411467 | biostudies-literature
Project description:The major objective of this study was to investigate the anti-chronic nonbacterial prostatitis (CNP) mechanism of T. patula by metabolomics and network pharmacology. The study demonstrated that the flavonoids and polysaccharides of T. patula could alleviate prostatitis by improving the level of DHT, reducing the secretion of PSA and TNF-α. Besides, both could enhance Na+/K+-ATPase activity, decrease the O2 consumption, CO2 production, heat production, energy expenditure of rats and promote respiratory exchange ratio of rats. Up to 28 potential biomarkers and 8 key metabolic pathways related to the treatment of CNP were elucidated by the metabolomics analysis, including phenylalanine metabolism, taurine and hypotaurine metabolism, tryptophan metabolism etc. Network pharmacology prediction also reflected the potential mechanism was associated with tryptophan metabolism and energy pathway. Generally, the potential anti-CNP mechanism of flavonoids and polysaccharides of T. patula might be through reducing the expression of inflammation factors, adjusting the level of hormone and regulating the amino acid metabolism, energy metabolism and glucose and lipid metabolism.
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Project description:BackgroundChuankezhi injection (CKZI) was an effective traditional Chinese medicine (TCM) injection in adjuvant bronchial asthma therapy. In this report, we used a network pharmacology method to reveal the mechanisms of CKZI for the treatment of asthma.MethodsThe candidate compounds in CKZI were determined by searching the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and China National Knowledge Infrastructure website (CNKI). The targets of candidate compounds were searched in the TCMSP, DrugBank 5.0, and SwissTargetPrediction. The disease targets were screened from the Online Mendelian Inheritance in Man (OMIM) and GeneCards. The overlapping gene symbols between candidate compounds and disease were filtered via a Venn diagram and were considered as potential targets. A protein-protein interaction (PPI) network and disease-related candidate compound-target-pathway (DC-T-P) network were visualized by Cytoscape 3.6.1. Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed by metascape to determine the pathways related to asthma.ResultsA total of 70 overlapping gene symbols were recognized as potential targets. Cytokines (IL6, TNF, and IL1B) and chemokines (CXCL8 and CCL2) could be recognized as hub genes. Asthma-related candidate compounds were mainly flavonoids, such as quercetin, luteolin, and kaempferol. The cytokine-mediated signaling pathway, cytokine receptor binding, and membrane craft were the most significant biological process (BP), molecular function (MF), and cellular component (CC) of GO function results, respectively. The relevant pathways of CKZI against asthma mainly include IL-17, NF-kappa B, HIF-1, calcium, and PI3K-Akt signaling pathways.ConclusionOur research provided a theoretical basis for further investigating the mechanisms of CKZI in the treatment of asthma.
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