title: Efficient discovery of abundant post-translational modifications and spectral pairs using peptide mass and retention time differences.
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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, PR China. yfu@ict.ac.cn
authors.forename: Yan
authors.initials: Y
authors.lastname: Fu
authors.forename: Wei
authors.initials: W
authors.lastname: Jia
authors.forename: Zhuang
authors.initials: Z
authors.lastname: Lu
authors.forename: Haipeng
authors.initials: H
authors.lastname: Wang
authors.forename: Zuofei
authors.initials: Z
authors.lastname: Yuan
authors.forename: Hao
authors.initials: H
authors.lastname: Chi
authors.forename: You
authors.initials: Y
authors.lastname: Li
authors.forename: Liyun
authors.initials: L
authors.lastname: Xiu
authors.forename: Wenping
authors.initials: W
authors.lastname: Wang
authors.forename: Chao
authors.initials: C
authors.lastname: Liu
authors.forename: Leheng
authors.initials: L
authors.lastname: Wang
authors.forename: Ruixiang
authors.initials: R
authors.lastname: Sun
authors.forename: Wen
authors.initials: W
authors.lastname: Gao
authors.forename: Xiaohong
authors.initials: X
authors.lastname: Qian
authors.forename: Si-Min
authors.initials: SM
authors.lastname: He
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D013058:Mass Spectrometry / Q000379:methods*; D008970:Molecular Weight; D010455:Peptides / Q000032:analysis / Q000737:chemistry*; D011499:Protein Processing, Post-Translational; D020539:Sequence Analysis, Protein
chemical_list: D010455:Peptides