糖肽
糖蛋白组学
数据库搜索引擎
化学
图形
聚糖
搜索算法
计算机科学
生物化学
计算生物学
生物
组合数学
搜索引擎
理论计算机科学
情报检索
算法
数学
糖蛋白
抗生素
作者
Lei Lü,Nicholas M. Riley,Michael R. Shortreed,Carolyn R. Bertozzi,Lloyd M. Smith
出处
期刊:Nature Methods
[Springer Nature]
日期:2020-10-26
卷期号:17 (11): 1133-1138
被引量:116
标识
DOI:10.1038/s41592-020-00985-5
摘要
We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus . O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. It also introduces a classification scheme to unify data reporting for glycoproteomics.
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