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Efficient discovery of abundant post-translational modifications and spectral pairs using peptide mass and retention time differences.

Authors :
Yan Fu
Wei Jia
Zhuang Lu
Haipeng Wang
Zuofei Yuan
Hao Chi
You Li
Liyun Xiu
Wenping Wang
Chao Liu
Leheng Wang
Ruixiang Sun
Wen Gao
Xiaohong Qian
Si-Min He
Source :
BMC Bioinformatics. 2009 Supplement 1, Vol. 10, Special section p1-12. 12p. 4 Charts, 4 Graphs.
Publication Year :
2009

Abstract

Background: Peptide identification via tandem mass spectrometry is the basic task of current proteomics research. Due to the complexity of mass spectra, the majority of mass spectra cannot be interpreted at present. The existence of unexpected or unknown protein post-translational modifications is a major reason. Results: This paper describes an efficient and sequence database-independent approach to detecting abundant post-translational modifications in high-accuracy peptide mass spectra. The approach is based on the observation that the spectra of a modified peptide and its unmodified counterpart are correlated with each other in their peptide masses and retention time. Frequently occurring peptide mass differences in a data set imply possible modifications, while small and consistent retention time differences provide orthogonal supporting evidence. We propose to use a bivariate Gaussian mixture model to discriminate modification-related spectral pairs from random ones. Due to the use of two-dimensional information, accurate modification masses and confident spectral pairs can be determined as well as the quantitative influences of modifications on peptide retention time. Conclusion: Experiments on two glycoprotein data sets demonstrate that our method can effectively detect abundant modifications and spectral pairs. By including the discovered modifications into database search or by propagating peptide assignments between paired spectra, an average of 10% more spectra are interpreted. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712105
Volume :
10
Database :
Academic Search Index
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
54372930
Full Text :
https://doi.org/10.1186/1471-2105-10-S1-S50