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通过经验优化,开发针对蛋白质组学的选定反应监测方法。

The development of selected reaction monitoring methods for targeted proteomics via empirical refinement.

机构信息

Department of Genome Sciences, University of Washington, Seattle, WA, USA.

出版信息

Proteomics. 2012 Apr;12(8):1134-41. doi: 10.1002/pmic.201200042.

Abstract

Software advancements in the last several years have had a significant impact on proteomics from method development to data analysis. Herein, we detail a method, which uses our in-house developed software tool termed Skyline, for empirical refinement of candidate peptides from targeted proteins. The method consists of four main steps from generation of a testable hypothesis, method development, peptide refinement, to peptide validation. The ultimate goal is to identify the best performing peptide in terms of ionization efficiency, reproducibility, specificity, and chromatographic characteristics to monitor as a proxy for protein abundance. It is important to emphasize that this method allows the user to perform this refinement procedure in the sample matrix and organism of interest with the instrumentation available. Finally, the method is demonstrated in a case study to determine the best peptide to monitor the abundance of surfactant protein B in lung aspirates.

摘要

在过去的几年中,软件的进步对蛋白质组学产生了重大影响,从方法开发到数据分析。在这里,我们详细介绍了一种方法,该方法使用我们内部开发的软件工具 Skyline,从靶向蛋白质中对候选肽进行经验性优化。该方法主要包括四个步骤,从生成可测试假设、方法开发、肽优化到肽验证。最终目标是根据离子化效率、重现性、特异性和色谱特性来识别性能最佳的肽,以作为监测蛋白质丰度的替代物。重要的是要强调的是,该方法允许用户在感兴趣的样本基质和生物体中使用可用的仪器进行此优化过程。最后,该方法通过一个案例研究进行了演示,以确定监测肺抽吸物中表面活性剂蛋白 B 丰度的最佳肽。

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