IEEE/ACM Trans Comput Biol Bioinform. 2019 Mar-Apr;16(2):388-395. doi: 10.1109/TCBB.2017.2701819. Epub 2017 May 5.
Glycosylation is a frequently observed post-translational modification on proteins. Currently, tandem mass spectrometry (MS/MS) serves as an efficient analytical technique for characterizing structures of oligosaccharides. However, developing effective computational approaches for identifying glycan structures from mass spectra is still a great challenge in glycoproteomics research. In this study, we proposed an approach for matching the input spectra with glycan structures acquired from a glycan structure database by incorporating a de novo sequencing assisted ranking scheme. The proposed approach is implemented as a software tool, GlycoNovoDB, for automated glycan structure identification from HCD MS/MS of glycopeptides. Experimental results showed that GlycoNovoDB can identify glycans effectively and has better performance than our previously proposed de novo sequencing algorithm as well as another software GlycoMaster DB.
糖基化是蛋白质上常见的一种翻译后修饰。目前，串联质谱（MS/MS）是一种用于鉴定寡糖结构的有效分析技术。然而，开发有效的计算方法来从质谱中识别聚糖结构仍然是糖组学研究中的一个巨大挑战。在这项研究中，我们提出了一种通过结合从头测序辅助排序方案，将输入谱与从聚糖结构数据库中获得的聚糖结构相匹配的方法。所提出的方法被实现为一个软件工具 GlycoNovoDB，用于从糖肽的 HCD MS/MS 中自动鉴定聚糖结构。实验结果表明，GlycoNovoDB 可以有效地识别聚糖，并且比我们之前提出的从头测序算法以及另一个软件 GlycoMaster DB 具有更好的性能。
