Division of Membrane Transport and Drug Targeting, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai 980-8578, Japan.
J Pharm Sci. 2011 Sep;100(9):3547-59. doi: 10.1002/jps.22612. Epub 2011 May 10.
An understanding of the functional roles of proteins, for example, in drug absorption, distribution, metabolism, elimination, toxicity, and efficacy (ADMET/efficacy), is important for drug discovery and development. Equally, detailed information about protein expression is required. Recently, a new protein quantification method, called quantitative targeted absolute proteomics (QTAP), has been developed on the basis of separation and identification of protein digests by liquid chromatography-linked tandem mass spectrometry with multiple reaction monitoring. Target peptides for quantification are selected only from sequence information, so time-consuming procedures such as antibody preparation and protein purification are unnecessary. In this review, we introduce the technical features of QTAP and summarize its advantages with reference to recently reported results. These include the evaluation of species differences of blood-brain barrier protein levels among human, monkey, and mouse. The high selectivity of QTAP and its ability to quantify multiple proteins simultaneously make it possible to determine the absolute expression levels of many proteins in tissues and cells in both physiological and disease states. Knowledge of absolute expression amounts, together with data on intrinsic protein activity, allows us to reconstruct in vivo protein function, and this should be an efficient strategy to predict ADMET/efficacy of drug candidates in humans in various disease states.
例如,了解蛋白质在药物吸收、分布、代谢、消除、毒性和疗效(ADMET/疗效)中的功能作用对于药物发现和开发非常重要。同样,也需要详细的蛋白质表达信息。最近,一种新的蛋白质定量方法,称为定量靶向绝对蛋白质组学(QTAP),已经在基于液相色谱-串联质谱联用多反应监测对蛋白质消化物进行分离和鉴定的基础上发展起来。定量用的目标肽段仅从序列信息中选择,因此不需要抗体制备和蛋白质纯化等耗时的程序。在这篇综述中,我们介绍了 QTAP 的技术特点,并参考最近的报道结果总结了其优点。其中包括评估人类、猴和鼠血脑屏障蛋白水平的种间差异。QTAP 的高选择性及其同时定量多种蛋白质的能力,使得在生理和疾病状态下定量组织和细胞中许多蛋白质的绝对表达水平成为可能。绝对表达量的知识,以及内在蛋白质活性的数据,使我们能够重建体内蛋白质功能,这应该是一种有效的策略,可以预测各种疾病状态下人体候选药物的 ADMET/疗效。