Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Germany.
BMC Bioinformatics. 2012;13 Suppl 16(Suppl 16):S8. doi: 10.1186/1471-2105-13-S16-S8. Epub 2012 Nov 5.
Selected reaction monitoring (SRM)-based proteomics approaches enable highly sensitive and reproducible assays for profiling of thousands of peptides in one experiment. The development of such assays involves the determination of retention time, detectability and fragmentation properties of peptides, followed by an optimal selection of transitions. If those properties have to be identified experimentally, the assay development becomes a time-consuming task. We introduce a computational framework for the optimal selection of transitions for a given set of proteins based on their sequence information alone or in conjunction with already existing transition databases. The presented method enables the rapid and fully automated initial development of assays for targeted proteomics. We introduce the relevant methods, report and discuss a step-wise and generic protocol and we also show that we can reach an ad hoc coverage of 80 % of the targeted proteins. The presented algorithmic procedure is implemented in the open-source software package OpenMS/TOPP.
基于选择反应监测 (SRM) 的蛋白质组学方法能够在一次实验中对数千种肽进行高度敏感和可重复的分析。此类测定的开发涉及确定肽的保留时间、可检测性和碎片化特性,然后选择最佳的转换。如果这些特性必须通过实验来确定,那么测定的开发就变成了一项耗时的任务。我们引入了一种基于序列信息或与现有转换数据库相结合的计算框架,用于为给定的蛋白质集选择最佳的转换。该方法能够快速、全自动地为靶向蛋白质组学开发测定。我们介绍了相关的方法,报告并讨论了一个逐步的、通用的方案,并且还表明我们可以达到 80%的靶向蛋白质的特定覆盖率。所提出的算法过程在开源软件包 OpenMS/TOPP 中实现。