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基于定量质谱的蛋白质组学在模型指导药物开发时代:转化药理学中的应用及最佳实践建议。

Quantitative mass spectrometry-based proteomics in the era of model-informed drug development: Applications in translational pharmacology and recommendations for best practice.

机构信息

Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK; Clinical Pharmacy Department, Faculty of Pharmacy, Tanta University, Tanta, Egypt.

Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.

出版信息

Pharmacol Ther. 2019 Nov;203:107397. doi: 10.1016/j.pharmthera.2019.107397. Epub 2019 Jul 31.

Abstract

Quantitative translation of the fate and action of a drug in the body is facilitated by models that allow extrapolation of in vitro measurements (such as the rate of metabolism, active transport across membranes, inhibition of enzymes and receptor occupancy) to in vivo consequences (intensity and duration of drug effects). These models use various physiological parameters, including data that describe the expression levels of pharmacologically relevant enzymes, transporters and receptors in tissues and in vitro systems. Immunoquantification approaches have traditionally been used to determine protein expression levels, generally providing relative quantification data with compromised selectivity and reproducibility. More recently, the development of several quantitative proteomic techniques, fuelled by advances in state-of-the-art mass spectrometry, has led to generating a wealth of qualitative and quantitative data. These data are currently used for various quantitative systems pharmacology applications, with the ultimate goal of conducting virtual clinical trials to inform clinical studies, especially when assessments are difficult to conduct on patients. In this review, we explore available quantitative proteomic methods, discuss their main applications in translational pharmacology and offer recommendations for selecting and implementing proteomic techniques.

摘要

定量翻译药物在体内的命运和作用,需要借助模型来实现,这些模型可以将体外测量(如代谢率、跨膜主动转运、酶抑制和受体占有率)推断到体内后果(药物作用的强度和持续时间)。这些模型使用各种生理参数,包括描述组织和体外系统中与药理学相关的酶、转运体和受体表达水平的数据。免疫定量方法传统上用于确定蛋白质表达水平,通常提供选择性和重现性较差的相对定量数据。最近,几种定量蛋白质组学技术的发展,得益于最先进的质谱技术的进步,产生了大量定性和定量数据。这些数据目前用于各种定量系统药理学应用,最终目标是进行虚拟临床试验,为临床研究提供信息,特别是在难以对患者进行评估时。在这篇综述中,我们探讨了现有的定量蛋白质组学方法,讨论了它们在转化药理学中的主要应用,并为选择和实施蛋白质组学技术提供了建议。

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