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Vol. 11, Issue 2, 290-299, February 2001

METHODS
Efficiency of Database Search for Identification of Mutated and Modified Proteins via Mass Spectrometry

Pavel A. Pevzner,1,3 Zufar Mulyukov,1 Vlado Dancik,2 and Chris L Tang2

1 Department of Computer Science and Engineering, University of California, San Diego, California 92093, USA; 2 Millennium Pharmaceuticals, Cambridge, Massachusetts 02139, USA

Although protein identification by matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrometry, the question about reliability of such searches remains open. Absence of rigorous significance scores in MS/MS database search makes it difficult to discard random database hits and may lead to erroneous protein identification, particularly in the case of mutated or post-translationally modified peptides. This problem is especially important for high-throughput MS/MS projects when the possibility of expert analysis is limited. Thus, algorithms that sort out reliable database hits from unreliable ones and identify mutated and modified peptides are sought. Most MS/MS database search algorithms rely on variations of the Shared Peaks Count approach that scores pairs of spectra by the peaks (masses) they have in common. Although this approach proved to be useful, it has a high error rate in identification of mutated and modified peptides. We describe new MS/MS database search tools, MS-CONVOLUTION and MS-ALIGNMENT, which implement the spectral convolution and spectral alignment approaches to peptide identification. We further analyze these approaches to identification of modified peptides and demonstrate their advantages over the Shared Peaks Count. We also use the spectral alignment approach as a filter in a new database search algorithm that reliably identifies peptides differing by up to two mutations/modifications from a peptide in a database.

3 Corresponding author.

11:290-299 ©2001 by Cold Spring Harbor Laboratory Press  ISSN 1088-9051/01 $5.00
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