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使用模拟磷酸肽光谱库进行可靠的位点定位

Confident site localization using a simulated phosphopeptide spectral library.

作者信息

Suni Veronika, Imanishi Susumu Y, Maiolica Alessio, Aebersold Ruedi, Corthals Garry L

机构信息

†Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Tykistokatu 6, FI-20520 Turku, Finland.

‡Turku Centre for Computer Science, Joukahaisenkatu 3-5 B, FI-20520 Turku, Finland.

出版信息

J Proteome Res. 2015 May 1;14(5):2348-59. doi: 10.1021/acs.jproteome.5b00050. Epub 2015 Mar 27.

Abstract

We have investigated if phosphopeptide identification and simultaneous site localization can be achieved by spectral library searching. This allows taking advantage of comparison of specific spectral features, which would lead to improved discrimination of differential localizations. For building a library, we propose a spectral simulation strategy where all possible single phosphorylations can be simply and accurately (re)constructed on enzymatically dephosphorylated peptides, by predicting the diagnostic fragmentation events produced in beam-type CID. To demonstrate the performance of our approach, enriched HeLa phosphopeptides were dephosphorylated with alkaline phosphatase and analyzed with higher energy collisional dissociation (HCD), which were then used for creating a spectral library of simulated phosphopeptides. Spectral library searching using SpectraST was performed on data sets of synthetic phosphopeptides and the HeLa phosphopeptides, and subsequently compared to Mascot and Sequest database searching followed by phosphoRS and Ascore afforded localization, respectively. Our approach successfully led to accurate localization, and it outperformed other methods, when phosphopeptides were covered by the library. These results suggest that the searching with simulated spectral libraries serves as a crucial approach for both supplementing and validating the phosphorylation sites obtained by database searching and localization tools. For future development, simulation of multiply phosphorylated peptides remains to be implemented.

摘要

我们研究了通过谱图库搜索是否能够实现磷酸化肽段的鉴定及同时进行位点定位。这使得利用特定谱图特征的比较成为可能,而这将有助于更好地区分不同的定位情况。为构建一个库,我们提出了一种谱图模拟策略,通过预测在束型碰撞诱导解离(CID)中产生的诊断性碎裂事件,能够在酶促去磷酸化的肽段上简单且准确地(重新)构建所有可能的单磷酸化修饰。为证明我们方法的性能,用碱性磷酸酶对富集的HeLa磷酸化肽段进行去磷酸化处理,并采用高能碰撞解离(HCD)进行分析,然后将其用于创建模拟磷酸化肽段的谱图库。使用SpectraST对合成磷酸化肽段和HeLa磷酸化肽段数据集进行谱图库搜索,随后分别与 Mascot 和 Sequest 数据库搜索以及磷酸化位点定位工具 phosphoRS 和 Ascore 进行比较。当磷酸化肽段被库覆盖时,我们的方法成功实现了准确的定位,并且优于其他方法。这些结果表明,使用模拟谱图库进行搜索是补充和验证通过数据库搜索及定位工具获得的磷酸化位点的关键方法。对于未来的发展而言,多重磷酸化肽段的模拟仍有待实现。

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