A novel scoring schema for peptide identification by searching protein sequence databases using tandem mass spectrometry data.

BMC Bioinformatics
Zhuo ZhangRunsheng Chen

Abstract

Tandem mass spectrometry (MS/MS) is a powerful tool for protein identification. Although great efforts have been made in scoring the correlation between tandem mass spectra and an amino acid sequence database, improvements could be made in three aspects, including characterization ofpeaks in spectra, adoption of effective scoring functions and access to thereliability of matching between peptides and spectra. A novel scoring function is presented, along with criteria to estimate the performance confidence of the function. Through learning the typesof product ions and the probability of generating them, a hypothetic spectrum was generated for each candidate peptide. Then relative entropy was introduced to measure the similarity between the hypothetic and the observed spectra. Based on the extreme value distribution (EVD) theory, a threshold was chosen to distinguish a true peptide assignment from a random one. Tests on a public MS/MS dataset demonstrated that this method performs better than the well-known SEQUEST. A reliable identification of proteins from the spectra promises a more efficient application of tandem mass spectrometry to proteomes with high complexity.

References

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Citations

Feb 1, 2007·Analytical and Bioanalytical Chemistry·Mario Thevis, Wilhelm Schänzer
Mar 21, 2007·Analytical Chemistry·Jainab KhatunMorgan C Giddings
May 9, 2008·PLoS Computational Biology·Leo McHugh, Jonathan W Arthur
Apr 26, 2008·PLoS Computational Biology·Liping Wei, Jun Yu
Dec 5, 2015·Frontiers in Bioengineering and Biotechnology·Xiaoliang SunWolfram Weckwerth
Jan 4, 2007·Rapid Communications in Mass Spectrometry : RCM·Mario ThevisWilhelm Schänzer

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Software Mentioned

Protein Identifier (
MathType
MOWSE
PI
Tabb
Sonar
Mascot
SEQUEST
ProbID

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