低分辨率串联质谱中多肽电荷态的测定。

Aaron A Klammer, Christine C Wu, Michael J MacCoss, William Stafford Noble
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引用次数: 36

摘要

质谱法是一种特别有用的技术,可以快速、可靠地鉴定复杂混合物中的多肽和蛋白质。肽序列可以通过将观察到的串联质谱(MS/MS)与序列数据库中肽的理论谱相关联来鉴定。不幸的是,要进行这种搜索,肽的电荷必须是已知的,而目前的电荷状态测定算法只能区分单电荷和多电荷光谱:例如,区分+2和+3是不可靠的。因此,搜索软件被迫多次搜索多电荷谱。为了最大限度地降低这种低效率,我们提出了一种支持向量机(SVM),该支持向量机可以快速可靠地将多电荷光谱分类为具有+2或+3前体肽离子。通过对多电荷光谱进行分类,我们的搜索时间减少了40%,同时保持了从这些光谱中获得的99%的肽和99%的蛋白质鉴定的平均值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Peptide charge state determination for low-resolution tandem mass spectra.

Mass spectrometry is a particularly useful technology for the rapid and robust identification of peptides and proteins in complex mixtures. Peptide sequences can be identified by correlating their observed tandem mass spectra (MS/MS) with theoretical spectra of peptides from a sequence database. Unfortunately, to perform this search the charge of the peptide must be known, and current chargestate- determination algorithms only discriminate singlyfrom multiply-charged spectra: distinguishing +2 from +3, for example, is unreliable. Thus, search software is forced to search multiply-charged spectra multiple times. To minimize this inefficiency, we present a support vector machine (SVM) that quickly and reliably classifies multiplycharged spectra as having either a +2 or +3 precursor peptide ion. By classifying multiply-charged spectra, we obtain a 40% reduction in search time while maintaining an average of 99% of peptide and 99% of protein identifications originally obtained from these spectra.

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