A suboptimal algorithm for de novo peptide sequencing via tandem mass spectrometry

J Comput Biol. 2003;10(1):1-12. doi: 10.1089/106652703763255633.

Abstract

Tandem mass spectrometry has emerged to be one of the most powerful high-throughput techniques for protein identification. Tandem mass spectrometry selects and fragments peptides of interest into N-terminal ions and C-terminal ions, and it measures the mass/charge ratios of these ions. The de novo peptide sequencing problem is to derive the peptide sequences from given tandem mass spectral data of k ion peaks without searching against protein databases. By transforming the spectral data into a matrix spectrum graph G = (V, E), where |V| = O(k(2)) and |E| = O(k(3)), we give the first polynomial time suboptimal algorithm that finds all the suboptimal solutions (peptides) in O(p|E|) time, where p is the number of solutions. The algorithm has been implemented and tested on experimental data. The program is available at http://hto-c.usc.edu:8000/msms/menu/denovo.htm.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Algorithms*
  • Amino Acid Sequence
  • Animals
  • Blood Proteins
  • Cattle
  • Mass Spectrometry / methods*
  • Molecular Sequence Data
  • Peptides / chemistry*
  • Proteins / chemistry
  • Quality Control
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Sequence Analysis, Protein / methods*
  • Serum Albumin, Bovine / chemistry

Substances

  • Blood Proteins
  • Peptides
  • Proteins
  • Serum Albumin, Bovine