Spectral Dictionaries: Integrating de novo Peptide Sequencing with Database Search of Tandem Mass Spectra

peer-reviewed · Molecular & Cellular Proteomics · 2009

peer-reviewed · Molecular & Cellular Proteomics · 2009. Sangtae Kim et al. Database search tools identify peptides by matching tandem mass spectra against a protein database. We study…
Date 2009-01-01
Type peer-reviewed
Venue Molecular & Cellular Proteomics
Publisher Elsevier BV
Contribution adjacent
DOI 10.1074/mcp.M800103-MCP200
Citations (OpenAlex) 95
Venue 2-year citedness 4.17

Abstract

Database search tools identify peptides by matching tandem mass spectra against a protein database. We study an alternative approach when all plausible de novo interpretations of a spectrum (spectral dictionary) are generated and then quickly matched against the database. We present a new MS-Dictionary algorithm for efficiently generating spectral dictionaries and demonstrate that MS-Dictionary can identify spectra that are missed in the database search. We argue that MS-Dictionary enables proteogenomics searches in six-frame translation of genomic sequences that may be prohibitively time-consuming for existing database search approaches. We show that such searches allow one to correct sequencing errors and find programmed frameshifts.

Authors

  1. Sangtae Kim · University of California San Diego
  2. Nitin Gupta · University of California San Diego
  3. Nuno Bandeira · University of California San Diego
  4. Pavel A. Pevzner · Max Planck Institute of Molecular Cell Biology and Genetics, University of California San Diego, University of Southern California

Methods and tools

  • MS-Dictionary: Hybrid method that integrates de novo spectral dictionaries with database search of tandem mass spectra.

Cites (16)

Cited by (9)

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