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一种从高分辨碰撞诱导解离(HCD)光谱中进行聚糖结构从头测序的有效方法。

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

作者信息

Sun Weiping, Kuljanin Miljan, Pittock Paula, Ma Bin, Zhang Kaizhong, Lajoie Gilles A

出版信息

IEEE Trans Nanobioscience. 2016 Mar;15(2):177-84. doi: 10.1109/TNB.2016.2519861. Epub 2016 Jan 20.

Abstract

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.

摘要

由于其高通量和高灵敏度,质谱已成为蛋白质组学研究中广泛使用的分析技术。在这些应用中,一个特定的应用是表征聚糖结构。糖基化是蛋白质中经常发生的翻译后修饰,与人类健康相关。因此,开发有效的计算方法以从质谱数据中自动识别聚糖结构具有重要意义。在我们的研究中,我们用数学方法对聚糖从头测序问题进行了公式化,并提出了一种从N-连接糖肽的HCD MS/MS光谱中进行聚糖从头测序的启发式算法。该算法按照精心设计的路径进行,以从MS/MS光谱构建最佳匹配的树状结构。实验结果表明,我们提出的方法可以有效地从HCD MS/MS光谱中识别聚糖结构。

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