Kojak: Efficient Analysis of Chemically Cross-Linked Protein Complexes

被引:144
作者
Hoopmann, Michael R. [1 ]
Zelter, Alex [2 ]
Johnson, Richard S. [3 ]
Riffle, Michael [2 ]
MacCoss, Michael J. [3 ]
Davis, Trisha N. [2 ]
Moritz, Robert L. [1 ]
机构
[1] Inst Syst Biol, Seattle, WA 98109 USA
[2] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
[3] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
proteomics; cross-linking; mass spectrometry; protein structure; MASS-SPECTROMETRY; LINKING ANALYSIS; PEPTIDES; IDENTIFICATION; STRATEGIES; TOPOLOGIES; DISCOVERY;
D O I
10.1021/pr501321h
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Protein chemical cross-linking and mass spectrometry enable the analysis of protein protein interactions and protein topologies;, however, complicated cross-linked peptide spectra require specialized algorithms to identify interacting sites. The Kojak cross-linking software application is a new, efficient approach to identify cross-linked peptides, enabling large-scale analysis of protein protein interactions by chemical cross-linking techniques. The algorithm integrates spectral processing and scoring schemes adopted from traditional database search algorithms and can identify cross-linked peptides using many different chemical cross-linkers with of without heavy isotope labels. Kojak was used to analyze both novel and existing data sets and was compared to existing cross-linking algorithms. The algorithm provided increased cross-link identifications over existing algorithms and, equally importantly, the results in a fraction Of computational time. The Kojak algorithm is open-source; cross-platform, and freely available. This software provides both existing and new cross-linking researchers alike an effective way to derive additional cross-link identifications from new or existing data sets. For new users, it provides a simple-analytical resource resulting in more cross-link identifications than other Methods.
引用
收藏
页码:2190 / 2198
页数:9
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