Bioinformatics Advance Access published online on March 3, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti362
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1 Dept. of Biological Chemistry and Program in Bioinformatics, University of Michigan, 1301 Catherine St., Ann Arbor, MI 48109
* To whom correspondence should be addressed.
Motivation: Comparing tandem mass spectra (MSMS) against a known data set of protein sequences is a common method for identifying unknown proteins; however, the processing of tandem mass spectra by current software often limits certain applications, including comprehensive coverage of post-translational modifications, non-specific searches, and real-time searches to allow result-dependent instrument control. This problem deserves attention as new mass spectrometers provide the ability for higher throughput and as known protein data sets rapidly grow in size. New software algorithms need to be devised in order to address the performance issues of conventional MSMS protein data set-based protein identification. Methods: This manuscript describes a novel algorithm based on converting a collection of monoisotopic, centroided spectra to a new data structure, named "Peptide Finite State Machine", which may be used to rapidly search a known data set of protein sequences, regardless of the number of spectra searched or the number of potential modifications examined. The algorithm is verified using a set of commercially available tryptic digest protein standards analyzed using an ABI 4700 MALDI TOFTOF mass spectrometer, and a free, open-source Peptide Finite State Machine implementation. It is illustrated that a Peptide Finite State Machine can accurately search large collections of spectra against large data sets of protein sequences (e.g. NCBI nr) using a regular desktop PC; however, this paper only details the method for identifying peptide and subsequently protein candidates from a data set of known protein sequences. The concept of using a Peptide Finite State Machine as a peptide pre-screening technique for MSMS-based search engines is validated by using Peptide Finite State Machines with Mascot and XTandem. Availability: Complete source-code, documentation, and examples for the reference Peptide Finite State Machine implementation are publicly available at the Proteome Commons, http://www.proteomecommons.org, and source-code may be used both commercially and non-commercially as long as the original authors are credited for their work.
Received November 21, 2004
Revised February 25, 2005
Accepted February 26, 2005
Article
Fast tandem mass spectra-based protein identification regardless of the number of spectra or potential modifications examined
Jayson Falkner, E-mail: jfalkner{at}umich.edu
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