Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach.
Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach.
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使用网络药理学和反向对接方法阐明 torcetrapib 的脱靶效应
DOI：
10.1186/1752-0509-6-152
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发表时间：
2012-12-10
影响因子：
--
通讯作者：
Li X
中科院分区：
文献类型：
--
作者：
Fan S;Geng Q;Pan Z;Li X;Tie L;Pan Y;Li X
TorcetRapib是一种胆固醇酯转移蛋白(CETP)抑制剂，可提高高密度脂蛋白(HDL)胆固醇和降低低密度脂蛋白(LDL)胆固醇水平，已被证明可增加死亡率和与不良反应相关的心脏事件。然而，TorcetRapib的非靶向效应的潜在机制仍不清楚。在本研究中，我们开发了一种系统生物学方法，通过将人类重组的信号网络与公开可用的微阵列基因表达数据相结合，为TorcetRapib的非靶标副作用提供独特的见解。利用Cytoscape和三个插件(BisGenet、NetworkAnalyzer和ClusterONE)建立了上下文特定的药物-基因相互作用网络。基因本体(GO)分析采用David功能标注工具，途径丰富分析采用ToppFun聚类。此外，通过反向对接方法预测了TorcetRapib的潜在脱靶能力。总的来说，从综合信令网络中检索到10503个节点，从BisGenet插件中获得47660个互联关系。此外，通过基因芯片显著性分析(SAM)检测到TorcetRapib处理的肾上腺癌细胞中有388个基因显著上调。在构建了人类信号网络后，对过表达的微阵列基因进行了定位，以说明上下文特定的网络。随后，发现了三个显著的基因调控网络(GRN)模块，这三个模块与TorcetRapib的非靶标效应有关。GO分析戏剧性地反映了与TorcetRapib相关的过度代表的生物学过程，包括激活细胞死亡、细胞凋亡和调节RNA代谢过程。丰富的信号通路发现，T细胞活化中的IL-2受体β链、血小板衍生生长因子受体(PDGFR)β信号通路、IL2介导的信号通路、ErbB信号通路和肝细胞生长因子受体(HGFR，c-Met)介导的信号通路可能在TorcetRapib相关的心血管不良反应中起决定性作用。最后，在TorcetRapib和跨膜受体之间的电子对接中进行了反向对接算法来识别潜在的脱靶。这一筛选是基于丰富的信号网络分析进行的。我们的研究从系统生物学的角度对TorcetRapib相关的非靶向不良反应的生物学过程提供了独特的见解。特别是，我们强调了PDGFR、HGFR、IL-2受体和ErbB1酪氨酸激酶可能是直接脱靶的重要性，这与TorcetRapib的不良反应高度相关，值得进一步的实验验证。
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. 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. 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.
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影响因子：
9.1
作者：
El Chami, Hala;Hassoun, Paul M.
通讯作者：
Hassoun, Paul M.
DOI：
10.1152/ajpheart.1999.277.5.h2026
发表时间：
1999-11-01
影响因子：
4.8
作者：
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通讯作者：
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影响因子：
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作者：
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影响因子：
3.4
作者：
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影响因子：
14.9
作者：
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通讯作者：
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