Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM), Jacques Colinge, Vienna, Austria.
Proteomics Clin Appl. 2012 Jan;6(1-2):102-16. doi: 10.1002/prca.201100077. Epub 2011 Dec 27.
Drugs induce global perturbations at the molecular machinery level because their cognate targets are involved in multiple biological functions or because of off-target effects. The analysis or the prediction of such systems level consequences of drug treatment therefore requires the application of systems biology concepts and methods. In this review, we first summarize the methods of chemical proteomics that can measure unbiased and proteome-wide drug protein target spectra, which is an obvious necessity to perform a global analysis. We then focus on the introduction of computational methods and tools to relate such target spectra to global models such as pathways and networks of protein-protein interactions, and to integrate them with existing protein functional annotations. In particular, we discuss how drug treatment can be mapped onto likely affected biological functions, how this can help identifying drug mechanisms of action, and how such mappings can be exploited to predict potential side effects and to suggest new indications for existing compounds.
药物会在分子机制层面引起全局干扰，原因是其相应的靶标涉及多种生物功能，或者是因为脱靶效应。因此，药物治疗的此类系统层面后果的分析或预测需要应用系统生物学的概念和方法。在这篇综述中，我们首先总结了化学蛋白质组学的方法，这些方法可以测量无偏和全蛋白质组范围的药物蛋白靶标谱，这是进行全局分析的明显必要条件。然后，我们重点介绍了将此类靶标谱与通路和蛋白质相互作用网络等全局模型相关联的计算方法和工具，并将其与现有的蛋白质功能注释进行整合。特别是，我们讨论了如何将药物治疗映射到可能受影响的生物功能上，这如何有助于确定药物的作用机制，以及如何利用这种映射来预测潜在的副作用，并为现有化合物提出新的适应症。
