Spectral Profiles, a Novel Representation of Tandem Mass Spectra and Their Applications for de Novo Peptide Sequencing and Identification*S⃞

摘要

Despite many efforts in the last decade, the progress in de novo peptide sequencing has been slow with only 30–45% of all peptides correctly reconstructed. We argue that accurate full-length peptide sequencing may be an unattainable goal for some spectra and demonstrate how to accurately sequence gapped peptides instead. We further argue that gapped peptides are nearly as useful as full-length peptides for error-tolerant database searches. Gapped peptides occupy a niche between long but inaccurate full-length reconstructions and short but accurate peptide sequence tags. Our MS-Profile tool uses spectral profiles, a new representation of tandem mass spectra, to generate gapped peptides that are longer and more accurate than peptide sequence tags of length 3 traditionally used to speed up database searches in proteomics. In addition, spectral profiles also enable intuitive visualization of all high scoring de novo reconstructions of tandem mass spectra.