Go Eden P, Rebecchi Kathryn R, Dalpathado Dilusha S, Bandu Mary L, Zhang Ying, Desaire Heather
Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, USA.
Anal Chem. 2007 Feb 15;79(4):1708-13. doi: 10.1021/ac061548c.
Mass spectrometry is emerging as a versatile analytical tool for profiling glycan and glycopeptide structures. While the interpretation of MS data remains a challenging and difficult task, substantial efforts have been made to develop informatics tools to alleviate MS data interpretation. Here, we present a web-based tool, GlycoPep DB, designed to facilitate compositional assignment for glycopeptides by comparing experimentally measured masses to all calculated glycopeptide masses from a carbohydrate database with N-linked glycans. GlycoPep DB is an advance over current tools to assign N-linked glycans because it uses a concept of "smart searching", where only biologically relevant carbohydrate compositions are searched, when matching carbohydrate compositions with the MS data making glycopeptide compositional assignment more efficient. This is in contrast to currently used tools, where many implausible glycan structures are present in the search output, but fewer biologically relevant glycan motifs are predicted. The utility of GlycoPep DB is illustrated in the analysis of glycopeptides derived from a proteolytic digest of follicle stimulating hormone.
质谱正逐渐成为一种用于分析聚糖和糖肽结构的多功能分析工具。虽然质谱数据的解读仍然是一项具有挑战性和困难的任务，但人们已经做出了大量努力来开发信息学工具，以减轻质谱数据解读的负担。在此，我们展示了一种基于网络的工具GlycoPep DB，其设计目的是通过将实验测量的质量与来自具有N-连接聚糖的碳水化合物数据库中所有计算出的糖肽质量进行比较，来促进糖肽的组成分配。GlycoPep DB相对于当前用于分配N-连接聚糖的工具是一个进步，因为它使用了“智能搜索”的概念，即在将碳水化合物组成与质谱数据匹配时，只搜索生物学上相关的碳水化合物组成，从而使糖肽组成分配更加高效。这与目前使用的工具形成对比，在目前的工具中，搜索输出中存在许多不合理的聚糖结构，但预测的生物学上相关的聚糖基序较少。GlycoPep DB的实用性在对促卵泡激素蛋白水解消化产生的糖肽的分析中得到了体现。
