An Effective Approach for Glycan Structure De Novo Sequencing From HCD Spectra

Mass spectrometry has become a widely used analytical technique for proteomics study because of its high throughput and sensitivity. Among those applications, a specific one is to characterize glycan structure. Glycosylation is a frequently occurred post-translational modification of proteins which is relevant to humans' health. Therefore, it is significant to develop effective computational methods to automate the identification of glycan structures from mass spectral data. In our research, we mathematically formulated the glycan de novo sequencing problem and proposed a heuristic algorithm for glycan de novo sequencing from HCD MS/MS spectra of N-linked glycopeptides. The algorithm proceeds in a carefully designate pathway to construct the best matched tree structure from MS/MS spectrum. Experimental results showed that our proposed approach can effectively identify glycan structures from HCD MS/MS spectra.