OPTIMIZING SEARCH CONDITIONS FOR THE MASS FINGERPRINT-BASED ID OF PROTEINS

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 通过使用 MS 数据搜索蛋白质序列集合进行蛋白质鉴定的两个核心问题是实验信息的最佳使用，以允许鉴定低丰度蛋白质以及准确分配结果错误的概率。对于基于MS的蛋白质全面鉴定，有必要选择合适的算法和最佳搜索条件。我们报告了使用概率算法在不同序列收集搜索条件下基于 PMF 的蛋白质鉴定质量的系统研究，该算法为每个结果分配统计显着性。我们采用了来自 2-DE 分离的人血浆蛋白的 2244 个 PMF，并在各种搜索限制下进行了鉴定：质量准确度 (0.01-0.3 Da)、遗漏切割位点的最大数量 (0-2) 以及搜索的序列集合的大小 (5.6 x 10(4)-1.8 x 10(5)）。通过计算每个条件的显着结果数量（显着性水平 0.05、0.01 和 0.001），我们证明了搜索条件对蛋白质组分析实验成功结果的影响。测试了利用白蛋白匹配肽的质量偏差的质量校正程序，试图提高鉴定的统计显着性，并且采用迭代搜索来鉴定来自每个PMF的多种蛋白质。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The two central problems in protein identification by searching a protein sequence collection with MS data are the optimal use of experimental information to allow for identification of low abundance proteins and the accurate assignment of the probability that a result is false. For comprehensive MS-based protein identification, it is necessary to choose an appropriate algorithm and optimal search conditions. We report a systematic study of the quality of PMF-based protein identifications under different sequence collection search conditions using the Probability algorithm, which assigns the statistical significance to each result. We employed 2244 PMFs from 2-DE-separated human blood plasma proteins, and performed identification under various search constraints: mass accuracy (0.01-0.3 Da), maximum number of missed cleavage sites (0-2), and size of the sequence collection searched (5.6 x 10(4)-1.8 x 10(5)). By counting the number of significant results (significance levels 0.05, 0.01, and 0.001) for each condition, we demonstrate the search condition impact on the successful outcome of proteome analysis experiments. A mass correction procedure utilizing mass deviations of albumin matching peptides was tested in an attempt to improve the statistical significance of identifications and iterative searching was employed for identification of multiple proteins from each PMF.