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Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach.

ABSTRACT: BACKGROUND: Torcetrapib, a cholesteryl ester transfer protein (CETP) inhibitor which raises high-density lipoprotein (HDL) cholesterol and reduces low-density lipoprotein (LDL) cholesterol level, has been documented to increase mortality and cardiac events associated with adverse effects. However, it is still unclear the underlying mechanisms of the off-target effects of torcetrapib. RESULTS: In the present study, we developed a systems biology approach by combining a human reassembled signaling network with the publicly available microarray gene expression data to provide unique insights into the off-target adverse effects for torcetrapib. Cytoscape with three plugins including BisoGenet, NetworkAnalyzer and ClusterONE was utilized to establish a context-specific drug-gene interaction network. The DAVID functional annotation tool was applied for gene ontology (GO) analysis, while pathway enrichment analysis was clustered by ToppFun. Furthermore, potential off-targets of torcetrapib were predicted by a reverse docking approach. In general, 10503 nodes were retrieved from the integrative signaling network and 47660 inter-connected relations were obtained from the BisoGenet plugin. In addition, 388 significantly up-regulated genes were detected by Significance Analysis of Microarray (SAM) in adrenal carcinoma cells treated with torcetrapib. After constructing the human signaling network, the over-expressed microarray genes were mapped to illustrate the context-specific network. Subsequently, three conspicuous gene regulatory networks (GRNs) modules were unearthed, which contributed to the off-target effects of torcetrapib. GO analysis reflected dramatically over-represented biological processes associated with torcetrapib including activation of cell death, apoptosis and regulation of RNA metabolic process. Enriched signaling pathways uncovered that IL-2 Receptor Beta Chain in T cell Activation, Platelet-Derived Growth Factor Receptor (PDGFR) beta signaling pathway, IL2-mediated signaling events, ErbB signaling pathway and signaling events mediated by Hepatocyte Growth Factor Receptor (HGFR, c-Met) might play decisive characters in the adverse cardiovascular effects associated with torcetrapib. Finally, a reverse docking algorithm in silico between torcetrapib and transmembrane receptors was conducted to identify the potential off-targets. This screening was carried out based on the enriched signaling network analysis. CONCLUSIONS: Our study provided unique insights into the biological processes of torcetrapib-associated off-target adverse effects in a systems biology visual angle. In particular, we highlighted the importance of PDGFR, HGFR, IL-2 Receptor and ErbB1tyrosine kinase might be direct off-targets, which were highly related to the unfavorable adverse effects of torcetrapib and worthy of further experimental validation.

SUBMITTER: Fan S

PROVIDER: S-EPMC3547811 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach.

Fan Shengjun S Geng Qiang Q Pan Zhenyu Z Li Xin X Tie Lu L Pan Yan Y Li Xuejun X

BMC systems biology 20121210

<h4>Background</h4>Torcetrapib, a cholesteryl ester transfer protein (CETP) inhibitor which raises high-density lipoprotein (HDL) cholesterol and reduces low-density lipoprotein (LDL) cholesterol level, has been documented to increase mortality and cardiac events associated with adverse effects. However, it is still unclear the underlying mechanisms of the off-target effects of torcetrapib.<h4>Results</h4>In the present study, we developed a systems biology approach by combining a human reassemb ...[more]

PMID: 23228038

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Project description:BackgroundThis study aimed to investigate the molecular mechanism of Tongfengding capsule (TFDC) in treating immune-inflammatory diseases of gouty arthritis (GA) and interleukin-1-beta (IL-1β) inhibitors by using network pharmacology, molecular docking, and cell experiments.MethodsIn this study, the compounds of TFDC and the potential inflammatory targets of GA were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Online Mendelian Inheritance in Man (OMIM), and GeneCards databases. The TFDC-GA-potential targets interaction network was accomplished by the STRING database. The TFDC-active compound-potential target-GA network was constructed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to further explore the GA mechanism and therapeutic effects of TFDC. Quantitative real-time PCR (qPCR) was used to verify whether the TFDC inhibited IL-1β in GA. Molecular docking technology was used to analyze the optimal effective compounds from the TFDC for docking with IL-1β.Result133 active compounds and 242 targets were screened from the TFDC, and 25 of the targets intersected with GA inflammatory targets, which were considered as potential therapeutic targets. Network pharmacological analysis showed that the TFDC active compounds such as quercetin, stigmasterol, betavulgarin, rutaecarpine, naringenin, dihydrochelerythrine, and dihydrosanguinarine had better correlation with GA inflammatory targets such as PTGS2, PTGS1, NOS2, SLC6A3, HTR3A, PPARG, MAPK14, RELA, MMP9, and MMP2. The immune-inflammatory signaling pathways of the active compounds for treating GA are IL-17 signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, HIF-1 signaling pathway, etc. The TFDC reduced IL-1β mRNA expression in GA by qPCR. Molecular docking results suggested that rutaecarpine was the most appropriate natural IL-1β inhibitor.ConclusionOur findings provide an essential role and bases for further immune-inflammatory studies on the molecular mechanisms of TFDC and IL-1β inhibitors development in GA.

Project description:Hawthorn leaves, which is a traditional Chinese medicine (TCM), has been used for treating coronary heart disease (CHD) for a long time in China. But the limited understanding of the main active components and molecular mechanisms of this traditional medicine has restricted its application and further research. The active compounds of hawthorn leaves were obtained from TCMSP database and SymMap database. The targets of it were predicted based on TCMSP, PubChem, Swiss Target Prediction, and SymMap database. The putative targets of CHD were gathered from multi-sources databases including the Online Mendelian Inheritance in Man (OMIM) database, the DrugBank database, the GeneCards database and the DisGeNet database. Network topology analysis, GO and KEGG pathway enrichment analyses were performed to select the key targets and pathways. Molecular docking was performed to demonstrate the binding capacity of the key compounds to the predicted targets. Furthermore, RAW264.7 cells stimulated by lipopolysaccharides (LPS) were treated with three effective compounds of hawthorn leaves to assess reliability of prediction. Quercetin, isorhamnetin and kaempferol were main active compounds in hawthorn leaves. Forty four candidate therapeutic targets were identified to be involved in protection of hawthorn leaves against CHD. Additionally, the effective compounds of it had good binding affinities to PTGS2, EGFR, and MMP2. Enrichment analyses suggested that immune inflammation related biological processes and pathways were possibly the potential mechanism. Besides, we found that three predicted effective compounds of hawthorn leaves decreased protein expression of PTGS2, MMP2, MMP9, IL6, IL1B, TNFα and inhibited activation of macrophage. In summary, the present study demonstrates that quercetin, kaempferol and isorhamnetin are proved to be the main effective compounds of hawthorn leaves in treatment of CHD, possibly by suppressing expression of PTGS2, MMP2, MMP9, inflammatory cytokines and macrophages viability. This study provides a new understanding of the active components and mechanisms of hawthorn leaves treating CHD from the perspective of network pharmacology.

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Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach.

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Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach.

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