PhosphoHunter:一个高效的磷酸肽鉴定软件工具。

Q1 Biochemistry, Genetics and Molecular Biology
Advances in Bioinformatics Pub Date : 2015-01-01 Epub Date: 2015-01-12 DOI:10.1155/2015/382869
Alessandra Tiengo, Lorenzo Pasotti, Nicola Barbarini, Paolo Magni
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引用次数: 2

摘要

磷酸化是一种蛋白质翻译后修饰。由于其“分子开关”的作用,它负责疾病相关途径的激活/失活。磷酸化蛋白的研究成为蛋白质组学分析的重点,以确定诊断/治疗靶点。液相色谱-串联质谱(LC-MS/MS)是应用最广泛的分析方法。虽然未经修饰的肽可以通过综合算法自动识别,但磷酸肽仍然需要自动化工具来避免耗时的人工解释。为了提高磷酸肽的识别效率,在Perl/C工具中开发并实现了一个新的程序,称为PhosphoHunter,这里提出并评估。它包括一个初步的启发式步骤,用于在序列鉴定之前过滤掉非磷酸化肽产生的MS/MS光谱。还制定了一种评估鉴定的磷酸肽的统计意义的方法。在1500 MS/MS光谱数据集上测试了PhosphoHunter的性能,并比较了另外两种工具:Mascot和Inspect。比较表明,PhosphoHunter的一个优点是灵敏度,这表明它能够以优越的性能识别真正的磷酸肽。性能指标依赖于单个参数(强度阈值),用户可以根据研究目标对其进行调整。这三种工具都定位了>90%的磷酸基。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

PhosphoHunter: An Efficient Software Tool for Phosphopeptide Identification.

PhosphoHunter: An Efficient Software Tool for Phosphopeptide Identification.

Phosphorylation is a protein posttranslational modification. It is responsible of the activation/inactivation of disease-related pathways, thanks to its role of "molecular switch." The study of phosphorylated proteins becomes a key point for the proteomic analyses focused on the identification of diagnostic/therapeutic targets. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the most widely used analytical approach. Although unmodified peptides are automatically identified by consolidated algorithms, phosphopeptides still require automated tools to avoid time-consuming manual interpretation. To improve phosphopeptide identification efficiency, a novel procedure was developed and implemented in a Perl/C tool called PhosphoHunter, here proposed and evaluated. It includes a preliminary heuristic step for filtering out the MS/MS spectra produced by nonphosphorylated peptides before sequence identification. A method to assess the statistical significance of identified phosphopeptides was also formulated. PhosphoHunter performance was tested on a dataset of 1500 MS/MS spectra and it was compared with two other tools: Mascot and Inspect. Comparisons demonstrated that a strong point of PhosphoHunter is sensitivity, suggesting that it is able to identify real phosphopeptides with superior performance. Performance indexes depend on a single parameter (intensity threshold) that users can tune according to the study aim. All the three tools localized >90% of phosphosites.

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来源期刊
Advances in Bioinformatics
Advances in Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
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