有效解决肽段谱匹配中的复杂蛋白质组搜索空间问题。
Effectively addressing complex proteomic search spaces with peptide spectrum matching.
机构信息
Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.
出版信息
Bioinformatics. 2013 May 15;29(10):1343-4. doi: 10.1093/bioinformatics/btt106. Epub 2013 Feb 27.
SUMMARY
Protein identification by mass spectrometry is commonly accomplished using a peptide sequence matching search algorithm, whose sensitivity varies inversely with the size of the sequence database and the number of post-translational modifications considered. We present the Spectrum Identification Machine, a peptide sequence matching tool that capitalizes on the high-intensity b1-fragment ion of tandem mass spectra of peptides coupled in solution with phenylisotiocyanate to confidently sequence the first amino acid and ultimately reduce the search space. We demonstrate that in complex search spaces, a gain of some 120% in sensitivity can be achieved.
AVAILABILITY
All data generated and the software are freely available for academic use at http://proteomics.fiocruz.br/software/sim.
CONTACT
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
通过质谱进行蛋白质鉴定通常使用肽序列匹配搜索算法来实现，其灵敏度与序列数据库的大小以及考虑的翻译后修饰数量成反比。我们提出了 Spectrum Identification Machine，这是一种肽序列匹配工具，它利用了与苯基异硫氰酸酯在溶液中偶联的肽的串联质谱中的高强度 b1-片段离子，从而能够自信地对第一个氨基酸进行测序，并最终缩小搜索空间。我们证明，在复杂的搜索空间中，可以提高约 120%的灵敏度。
可用性
所有生成的数据和软件均可在 http://proteomics.fiocruz.br/software/sim 上免费供学术使用。
联系方式
补充信息
补充数据可在 Bioinformatics 在线获得。
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