RT-PSM, a real-time program for peptide-spectrum matching with statistical significance.
The analysis of complex biological peptide mixtures by tandem mass spectrometry (MS/MS) produces a huge body of collision-induced dissociation (CID) MS/MS spectra. Several methods have been developed for identifying peptide-spectrum matches (PSMs) by assigning MS/MS spectra to peptides in a database. However, most of these methods either do not give the statistical significance of PSMs (e.g., SEQUEST) or employ time-consuming computational methods to estimate the statistical significance (e.g., PeptideProphet). In this paper, we describe a new algorithm, RT-PSM, which can be used to identify PSMs and estimate their accuracy statistically in real time. RT-PSM first computes PSM scores between an MS/MS spectrum and a set of candidate peptides whose masses are within a preset tolerance of the MS/MS precursor ion mass. Then the computed PSM scores of all candidate peptides are employed to fit the expectation value distribution of the scores into a second-degree polynomial function in PSM score. The statistical significance of the best PSM is estimated by extrapolating the fitting polynomial function to the best PSM score. RT-PSM was tested on two pairs of MS/MS spectrum datasets and protein databases to investigate its performance. The MS/MS spectra were acquired using an ion trap mass spectrometer equipped with a nano-electrospray ionization source. The results show that RT-PSM has good sensitivity and specificity. Using a 55,577-entry protein database and running on a standard Pentium-4, 2.8-GHz CPU personal computer, RT-PSM can process peptide spectra on a sequential, one-by-one basis in 0.047 s on average, compared to more than 7 s per spectrum on average for Sequest and X!Tandem, in their current batch-mode processing implementations. RT-PSM is clearly shown to be fast enough for real-time PSM assignment of MS/MS spectra generated every 3 s or so by a 3D ion trap or by a QqTOF instrument.
Wu
Fang-Xiang
FX
Health and Environment Unit, Laval University Medical Research Center (CHUL), Faculty of Medicine, 2705 Boul. Laurier, Quebec City, QC Canada, G1V 4G2.
Gagné
Pierre
P
Droit
Arnaud
A
Poirier
Guy G
GG
D000465:Algorithms; D003201:Computers; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D036103:Nanotechnology; D010455:Peptides / Q000737:chemistry*; D021241:Spectrometry, Mass, Electrospray Ionization; D053719:Tandem Mass Spectrometry / Q000706:statistics & numerical data*
D010455:Peptides