A new approach to protein identification

  • Authors:

  • Nuno Bandeira;Dekel Tsur;Ari Frank;Pavel Pevzner

  • Affiliations:

  • Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, CA

  • Venue:
  • RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
  • Year:
  • 2006

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Abstract

Advances in tandem mass-spectrometry (MS/MS) steadily increase the rate of generation of MS/MS spectra and make it more computationally challenging to analyze such huge datasets. As a result, the existing approaches that compare spectra against databases are already facing a bottleneck, particularly when interpreting spectra of post-translationally modified peptides. In this paper we introduce a new idea that allows one to perform MS/MS database search ... without ever comparing a spectrum against a database. The idea has two components: experimental and computational. Our experimental idea is counter- intuitive: we propose to intentionally introduce chemical damage to the sample. Although it does not appear to make any sense from the experimental perspective, it creates a large number of “spectral pairs” that, as we show below, open up computational avenues that were never explored before. Having a spectrum of a modified peptide paired with a spectrum of an unmodified peptide, allows one to separate the prefix and suffix ladders, to greatly reduce the number of noise peaks, and to generate a small number of peptide reconstructions that are very likely to contain the correct one. The MS/MS database search is thus reduced to extremely fast pattern matching (rather than time-consuming matching of spectra against databases). In addition to speed, our approach provides a new paradigm for identifying post-translational modifications.