Mutation-tolerant protein identification by mass-spectrometry

Authors:
Pavel A. Pevzner;Vlado Dančík;Chris L. Tang
Affiliations:
Departments of Mathematics, Computer Science, and Molecular Biology, University of Southern California, Los Angeles, CA;Millennium Pharmacauticals, 640 Memorial Dr, Cambridge, MA;Millennium Pharmacauticals, 640 Memorial Dr, Cambridge, MA
Venue:
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
Year:
2000

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Abstract

Database search in tandem mass spectrometry is a powerful tool for protein identification. High-throughput spectral acquisition raises the problem of dealing with genetic variation and peptide modifications within a population of related proteins. A method that cross-correlates and clusters related spectra in large collections of uncharacterized spectra (i.e from normal and diseased individuals) would be extremely valuable in functional proteomics. This problem is far from being simple since very similar peptides may have very different spectra. We introduce a new notion of spectral similarity that allows one to identify related spectra even if the corresponding peptides have multiple modifications/mutations. Based on this notion we developed a new algorithm for mutation-tolerant database search as well as a method for cross-correlating related uncharacterized spectra. The paper describes this new approach and its applications in functional proteomics.