Drug discovery using chemical systems biology: identification of the protein-ligand binding network to explain the side effects of CETP inhibitors.
Drug discovery using chemical systems biology: identification of the protein-ligand binding network to explain the side effects of CETP inhibitors.
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DOI：
10.1371/journal.pcbi.1000387
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发表时间：
2009-05
影响因子：
4.3
通讯作者：
Bourne PE
中科院分区：
文献类型：
--
作者：
Xie L;Li J;Xie L;Bourne PE
蛋白质-药物相互作用网络的系统鉴定对于将药物作用的复杂模式与临床适应症相关联至关重要。我们介绍了一种新的计算策略，以确定蛋白质-配体结合的基因组范围内的配置文件，并将其应用于阐明与胆固醇酯转移蛋白（CETP）抑制剂的药物不良反应的分子机制。CETP抑制剂是治疗心血管疾病的一类新的预防性疗法。然而，临床研究表明，一种CETP抑制剂Torcetrapib由于高血压而具有致命的脱靶效应，因此它已从III期临床试验中撤出。我们已经从人类结构基因组中确定了一组Torcetrapib和其他CETP抑制剂的脱靶点，并通过文献将这些靶标映射到生物学途径。预测的蛋白质-配体网络与来自多个来源的实验结果一致，并揭示了CETP抑制剂的副作用是通过多个相互连接的通路的组合控制来调节的。鉴于组合控制是在许多生物过程中观察到的常见现象，我们的研究结果表明，通过使用单一或多种疗法微调多种脱靶相互作用，可以最大限度地减少药物的不良反应。这项工作扩展了化学基因组学方法的范围，并阐明了系统生物学在药物发现中的作用。新药上市的成本和药物发现和开发过程后期的流失率都在增加。Torcetrapib就是一个很好的例子，经过15年的开发和8亿美元的估计成本，已经退出了III期临床试验。Torcetrapib代表了治疗心血管疾病的一类新疗法;然而，临床研究表明，由于高血压，Torcetrapib具有致命的副作用。为了了解Torcetrapib和其他正在进行临床试验的相关药物的这些药物不良反应的起源，我们引入了一种系统的策略来识别人类结构蛋白质组中的脱靶点，并使用生化途径分析来研究这些脱靶点在影响人体生理学和病理学中的作用。我们的研究结果表明，新药的潜在副作用可以在开发周期的早期阶段被发现，并通过微调多种脱靶相互作用来最大限度地减少。希望这可以降低药物开发成本和临床试验期间的死亡率。
Systematic identification of protein-drug interaction networks is crucial to correlate complex modes of drug action to clinical indications. We introduce a novel computational strategy to identify protein-ligand binding profiles on a genome-wide scale and apply it to elucidating the molecular mechanisms associated with the adverse drug effects of Cholesteryl Ester Transfer Protein (CETP) inhibitors. CETP inhibitors are a new class of preventive therapies for the treatment of cardiovascular disease. However, clinical studies indicated that one CETP inhibitor, Torcetrapib, has deadly off-target effects as a result of hypertension, and hence it has been withdrawn from phase III clinical trials. We have identified a panel of off-targets for Torcetrapib and other CETP inhibitors from the human structural genome and map those targets to biological pathways via the literature. The predicted protein-ligand network is consistent with experimental results from multiple sources and reveals that the side-effect of CETP inhibitors is modulated through the combinatorial control of multiple interconnected pathways. Given that combinatorial control is a common phenomenon observed in many biological processes, our findings suggest that adverse drug effects might be minimized by fine-tuning multiple off-target interactions using single or multiple therapies. This work extends the scope of chemogenomics approaches and exemplifies the role that systems biology has in the future of drug discovery. Both the cost to launch a new drug and the attrition rate during the late stage of the drug discovery and development process are increasing. Torcetrapib is a case in point, having been withdrawn from phase III clinical trials after 15 years of development and an estimated cost of US $800 M. Torcetrapib represents a new class of therapies for the treatment of cardiovascular disease; however, clinical studies indicated that Torcetrapib has deadly side-effects as a result of hypertension. To understand the origins of these adverse drug reactions from Torcetrapib and other related drugs undergoing clinical trials, we introduce a systematic strategy to identify off-targets in the human structural proteome and investigate the roles of these off-targets in impacting human physiology and pathology using biochemical pathway analysis. Our findings suggest that potential side-effects of a new drug can be identified at an early stage of the development cycle and be minimized by fine-tuning multiple off-target interactions. The hope is that this can reduce both the cost of drug development and the mortality rates during clinical trials.
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站点基础：用于基于结构的蛋白质 - 配体结合位点比较的数据库。
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14.9
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