Hu Han, Khatri Kshitij, Klein Joshua, Leymarie Nancy, Zaia Joseph
Center for Biomedical Mass Spectrometry, Boston University, Boston, MA, USA.
Bioinformatics Program, Boston University, Boston, MA, USA.
Glycoconj J. 2016 Jun;33(3):285-96. doi: 10.1007/s10719-015-9633-3. Epub 2015 Nov 26.
Despite the publication of several software tools for analysis of glycopeptide tandem mass spectra, there remains a lack of consensus regarding the most effective and appropriate methods. In part, this reflects problems with applying standard methods for proteomics database searching and false discovery rate calculation. While the analysis of small post-translational modifications (PTMs) may be regarded as an extension of proteomics database searching, glycosylation requires specialized approaches. This is because glycans are large and heterogeneous by nature, causing glycopeptides to exist as multiple glycosylated variants. Thus, the mass of the peptide cannot be calculated directly from that of the intact glycopeptide. In addition, the chemical nature of the glycan strongly influences product ion patterns observed for glycopeptides. As a result, glycopeptidomics requires specialized bioinformatics methods. We summarize the recent progress towards a consensus for effective glycopeptide tandem mass spectrometric analysis.
尽管已经发表了几种用于分析糖肽串联质谱的软件工具,但对于最有效和最合适的方法仍缺乏共识。部分原因在于,将蛋白质组学数据库搜索和错误发现率计算的标准方法应用于此存在问题。虽然对小的翻译后修饰(PTM)的分析可被视为蛋白质组学数据库搜索的扩展,但糖基化需要专门的方法。这是因为聚糖本质上体积大且具有异质性,导致糖肽以多种糖基化变体的形式存在。因此,无法直接从完整糖肽的质量计算出肽的质量。此外,聚糖的化学性质强烈影响糖肽所观察到的产物离子模式。结果,糖肽组学需要专门的生物信息学方法。我们总结了在有效糖肽串联质谱分析达成共识方面的最新进展。