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A stringent approach to improve the quality of nitrotyrosine peptide identifications.

机译:一种提高硝基酪氨酸肽鉴定质量的严格方法。

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摘要

Tyrosine nitration is the consequence of a complex machinery of formation and merging of oxygen and nitrogen radicals, and has been associated with both physiological pathways as well as with several human diseases. The latter turned this posttranslational protein modification into an interesting biomarker, being either a consequence of the disease or a factor contributing to the disease onset. However, the interpretation of MS and MS/MS data of peptides containing nitrotyrosine has proven to be very challenging and consequently, the risk of linking MS/MS spectra to incorrect peptide sequences exists and has been reported. Here, we discuss the causes of data misinterpretation and describe a general method to avoid mistakes of MS/MS spectrum misinterpretation. Central in our approach is the reduction of nitrotyrosine into aminotyrosine and the use of the Peptizer algorithm to inspect MS/MS quality-related assumptions.
机译:酪氨酸硝化是氧和氮自由基形成和合并的复杂机制的结果,并且已与生理途径以及多种人类疾病相关。后者将这种翻译后蛋白质修饰转变为有趣的生物标志物,这是疾病的结果或是导致疾病发作的因素。然而,事实证明,对含有硝基酪氨酸的肽段的MS和MS / MS数据进行解释非常具有挑战性,因此,存在将MS / MS谱图连接至错误的肽段序列的风险,并且已有报道。在这里,我们讨论数据误解的原因,并描述一种避免MS / MS频谱误解错误的通用方法。我们方法的核心是将硝基酪氨酸还原为氨基酪氨酸,并使用Peptizer算法检查与MS / MS质量相关的假设。

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