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串联质谱(MS/MS)数据库搜索算法概述。

Overview of tandem mass spectrometry (MS/MS) database search algorithms.

作者信息

Kapp Eugene, Schütz Frédéric

机构信息

Ludwig Institute for Cancer Research, Melbourne, Australia.

Swiss Institute of Bioinformatics, Lausanne, Switzerland.

出版信息

Curr Protoc Protein Sci. 2007 Aug;Chapter 25:25.2.1-25.2.19. doi: 10.1002/0471140864.ps2502s49.

Abstract

Mass spectrometry-based methods for the identification of proteins are fundamental platform technologies for proteomics. One comprehensive approach is to subject trypsinized peptides to tandem mass spectrometry (MS/MS) to obtain detailed structural information. Different strategies are available for interpreting MS/MS data and hence deducing the amino acid sequence of the peptides. The most common method is to use a search algorithm to identify peptides by correlating experimental and theoretical MS/MS data (the latter being generated from possible peptides in the protein sequence database). Identified peptides are collated and protein entries from the sequence database inferred. This unit focuses on the most widely used tandem MS peptide identification search algorithms (commercial and open source), their availability, ease of use, strengths, speed and scoring, as well as their relative sensitivity and specificity.

摘要

基于质谱的蛋白质鉴定方法是蛋白质组学的基础平台技术。一种全面的方法是将经胰蛋白酶消化的肽段进行串联质谱分析(MS/MS),以获得详细的结构信息。有不同的策略可用于解释MS/MS数据,从而推断肽段的氨基酸序列。最常用的方法是使用搜索算法,通过将实验性和理论性MS/MS数据(后者由蛋白质序列数据库中可能的肽段生成)进行关联来鉴定肽段。将鉴定出的肽段进行整理,并推断出序列数据库中的蛋白质条目。本单元重点介绍最广泛使用的串联质谱肽段鉴定搜索算法(商业和开源)、它们的可用性、易用性、优势、速度和评分,以及它们相对的灵敏度和特异性。

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