Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas 77573, USA.
J Proteome Res. 2013 Jul 5;12(7):3207-14. doi: 10.1021/pr4003382. Epub 2013 Jun 19.
The high mass accuracy and resolution of modern mass spectrometers provides new opportunities to employ theoretical peptide distributions in large-scale proteomic studies. We used theoretical distributions to study noise filtering and mass measurement errors and to examine mass-based differentiation of phosphorylated and nonphosphorylated peptides. Only the monoisotopic mass of the experimental precursor ion was necessary for this analysis. We found that peak deviations can be used to characterize the modification states of peptides in a sample. When applied to large-scale proteomic data sets, the peak deviation distribution can be used to filter chemical/electronic noise for singly charged species. Using peak deviation distributions, it is possible to separate the phosphorylated peptides from the nonphosphorylated peptides, enabling evaluation of the phosphoproteome content of a sample. Because this approach is simple, with light computational requirements, the analysis of theoretical peptide distributions has a significant potential for application to phosphoproteome analyses. For our studies we used publicly available data sets from three large-scale proteomic studies.
现代质谱仪具有高精度和高分辨率，为在大规模蛋白质组学研究中应用理论肽分布提供了新的机会。我们使用理论分布来研究噪声过滤和质量测量误差，并研究基于质量的磷酸化和非磷酸化肽的区分。这种分析只需要实验前体离子的单同位素质量。我们发现峰偏差可用于表征样品中肽的修饰状态。当应用于大规模蛋白质组学数据集时，峰偏差分布可用于过滤单电荷物种的化学/电子噪声。使用峰偏差分布，可以将磷酸化肽与非磷酸化肽分开，从而评估样品的磷酸化蛋白质组含量。由于这种方法简单，计算要求低，因此理论肽分布的分析在应用于磷酸化蛋白质组学分析方面具有很大的潜力。在我们的研究中，我们使用了三个大规模蛋白质组学研究中公开可用的数据。
