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蛋白质-蛋白质交联与人类健康:用质谱法阐明这一现象所面临的挑战。

Protein-protein cross-linking and human health: the challenge of elucidating with mass spectrometry.

机构信息

a Food & Bio-Based Products, AgResearch Ltd ., Lincoln , New Zealand.

b Biomolecular Interaction Centre , University of Canterbury , Christchurch , New Zealand.

出版信息

Expert Rev Proteomics. 2017 Oct;14(10):917-929. doi: 10.1080/14789450.2017.1362336. Epub 2017 Aug 4.

DOI:10.1080/14789450.2017.1362336
PMID:28759730
Abstract

In several biomedical research fields, the cross-linking of peptides and proteins has an important impact on health and wellbeing. It is therefore of crucial importance to study this class of post-translational modifications in detail. The huge potential of mass spectrometric technologies in the mapping of these protein-protein cross-links is however overshadowed by the challenges that the field has to overcome. Areas covered: In this review, we summarize the different pitfalls and challenges that the protein-protein cross-linking field is confronted with when using mass spectrometry approaches. We additionally focus on native disulfide bridges as an example and provide some examples of cross-links that are important in the biomedical field. Expert commentary: The current flow of methodological improvements, mainly from the chemical cross-linking field, has delivered a significant contribution to deciphering native and insult-induced cross-links. Although an automated data analysis of proteome-wide peptide cross-linking is currently only possible in chemical cross-linking experiments, the field is well on the way towards a more automated analysis of native and insult-induced cross-links in raw mass spectrometry data that will boost its potential in biomedical applications.

摘要

在几个生物医学研究领域中,肽和蛋白质的交联对健康和幸福有重要影响。因此,详细研究这类翻译后修饰至关重要。然而,质谱技术在绘制这些蛋白质-蛋白质交联物图谱方面具有巨大的潜力,但该领域需要克服的挑战也使其黯然失色。涵盖领域:在这篇综述中,我们总结了当使用质谱方法时,蛋白质-蛋白质交联领域所面临的不同陷阱和挑战。我们还特别关注天然二硫键,并提供了一些在生物医学领域重要的交联物的例子。专家评论:目前,主要来自化学交联领域的方法学改进正在为解析天然和应激诱导的交联物做出重大贡献。尽管目前在化学交联实验中才有可能对蛋白质组范围内的肽交联进行自动数据分析,但该领域正在朝着更自动化地分析原始质谱数据中的天然和应激诱导交联物的方向发展,这将提高其在生物医学应用中的潜力。

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