Zhang Yanlin, Yu Chuan-Yih, Song Ehwang, Li Shuai Cheng, Mechref Yehia, Tang Haixu, Liu Xiaowen
Department of Computer Science, City University of Hong Kong , Kowloon, Hong Kong.
Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis , Indianapolis, Indiana 46202, United States.
J Proteome Res. 2015 Dec 4;14(12):5099-108. doi: 10.1021/acs.jproteome.5b00299. Epub 2015 Nov 13.
Glycosylation is one of the most common post-translational modifications in proteins, existing in ~50% of mammalian proteins. Several research groups have demonstrated that mass spectrometry is an efficient technique for glycopeptide identification; however, this problem is still challenging because of the enormous diversity of glycan structures and the microheterogeneity of glycans. In addition, a glycopeptide may contain multiple glycosylation sites, making the problem complex. Current software tools often fail to identify glycopeptides with multiple glycosylation sites, and hence we present GlycoMID, a graph-based spectral alignment algorithm that can identify glycopeptides with multiple hydroxylysine O-glycosylation sites by tandem mass spectra. GlycoMID was tested on mass spectrometry data sets of the bovine collagen α-(II) chain protein, and experimental results showed that it identified more glycopeptide-spectrum matches than other existing tools, including many glycopeptides with two glycosylation sites.
糖基化是蛋白质中最常见的翻译后修饰之一,存在于约50%的哺乳动物蛋白质中。几个研究小组已经证明,质谱是一种用于糖肽鉴定的有效技术;然而,由于聚糖结构的巨大多样性和聚糖的微异质性,这个问题仍然具有挑战性。此外,一个糖肽可能包含多个糖基化位点,这使得问题变得复杂。当前的软件工具常常无法识别具有多个糖基化位点的糖肽,因此我们提出了GlycoMID,一种基于图谱的光谱比对算法,它可以通过串联质谱识别具有多个羟赖氨酸O-糖基化位点的糖肽。GlycoMID在牛胶原蛋白α-(II)链蛋白的质谱数据集上进行了测试,实验结果表明,它比其他现有工具识别出更多的糖肽-光谱匹配,包括许多具有两个糖基化位点的糖肽。