首页> 外文期刊>Glycobiology >De novo glycan structure search with the CID MS/MS spectra of native N-glycopeptides
【24h】

De novo glycan structure search with the CID MS/MS spectra of native N-glycopeptides

机译:使用天然N-糖肽的CID MS / MS光谱从头进行聚糖结构搜索

获取原文
获取原文并翻译 | 示例
       

摘要

The aim of our study is to automatically analyze the glycan and peptide structures of N-glycopeptides without a need to release glycans from the glycopeptides. Our wet laboratory raw data represent a series of MS/MS mass spectra obtained from a reverse-phase liquid chromatography run of size-exclusion-enriched tryptic-digested glycopeptides from glycoproteins. The MS/MS spectra are first analyzed in order to identify glycosylated peptides and N-glycan monosaccharide compositions present on each glycopeptide. We further developed a Branch-and-Bound algorithm to search de novo N-glycan structures, i.e., monosaccharide compositions and their ordered sequences from native glycopeptides. Our de novo algorithm is based on iterative growth and selection of a population of glycan structures and it does not use databases of known glycan structures. We validate the algorithm with (i) in silico-generated spectra, with or without deteriorating deletions, (ii) with a purified glycoprotein transferrin, and (iii) with a complex mixture of N-glycopeptides enriched from human plasma. Our Branch-and-Bound algorithm depicted glycan structures from all the above-mentioned three input data types. Due to the large diversity of glycan structures, the results typically contained several proposed structures matching almost equally well to the spectra. In conclusion, this algorithm automatically identifies glycopeptides and their structures from the MS/MS spectra and thus greatly reduces the number of possible glycan structures from the vast amount of potential ones.
机译:我们研究的目的是自动分析N-糖肽的聚糖和肽结构,而无需从糖肽中释放聚糖。我们的湿实验室原始数据代表了一系列的MS / MS质谱图,这些质谱图是通过反相液相色谱运行的,其中包含糖蛋白中富含大小排阻的胰蛋白酶消化的糖肽。首先分析MS / MS谱图,以鉴定每个糖肽上存在的糖基化肽和N-聚糖单糖成分。我们进一步开发了一种分支定界算法,以从天然糖肽中搜索从头开始的N-聚糖结构,即单糖组成及其有序序列。我们的从头算法基于迭代增长和糖基结构群的选择,并且不使用已知糖基结构的数据库。我们用(i)在计算机生成的光谱中验证该算法,无论有或没有恶化的缺失,(ii)用纯化的糖蛋白转铁蛋白,以及(iii)用从人血浆中富集的N-糖肽的复杂混合物。我们的“分支定界”算法从所有上述三种输入数据类型中描绘了聚糖结构。由于聚糖结构的多样性很大,结果通常包含几个提议的结构,它们与光谱几乎完全匹配。总之,该算法可从MS / MS光谱中自动识别糖肽及其结构,从而从大量潜在的糖结构中大大减少了可能的糖结构的数量。

著录项

  • 来源
    《Glycobiology》 |2009年第7期|p.707-714|共8页
  • 作者单位

    2Transplantation Laboratory &

    Infection Biology Research Program, Haartman Institute, University of Helsinki 3Applied Numerics Oy, Ltd, Helsinki 4Medicel Oy, Ltd, Espoo 5HUSLAB, Helsinki University Central Hospital, Helsinki, Finland;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号