Traditionally, peptide identification using fragmentation spectra relies on extracting the maximum amount of information from spectra. Using different combinations of small ion masses, we show that identifying a small number of fragment ions in a spectrum is sufficient for peptide identification. We consider y2-, y3-, b2-, and b3-ions and find the combination of b2-y2 to be sufficient for many peptides. Adding either the y3- or the b3-ion increases specificity and allows reliable peptide identification in the human proteome. Fragmentation spectra and peptides are represented as n-dimensional vectors, where n is given by the number of fragment ions considered, and the peptide mass. The identification score is given by the Euclidian distance between the spectra and the matching peptide in n-dimensional space. We show that this approach, using minimal information, allows for precise and fast peptide identification.
Peptide identification using vectors of small fragment ions / D. Cittaro, D. Borsotti, A. Maiolica, E. Argenzio, J. Rappsilber. - In: JOURNAL OF PROTEOME RESEARCH. - ISSN 1535-3893. - 4:3(2005 Apr 09), pp. 1006-1011. [10.1021/pr0500152]
Peptide identification using vectors of small fragment ions
E. ArgenzioPenultimo
;
2005
Abstract
Traditionally, peptide identification using fragmentation spectra relies on extracting the maximum amount of information from spectra. Using different combinations of small ion masses, we show that identifying a small number of fragment ions in a spectrum is sufficient for peptide identification. We consider y2-, y3-, b2-, and b3-ions and find the combination of b2-y2 to be sufficient for many peptides. Adding either the y3- or the b3-ion increases specificity and allows reliable peptide identification in the human proteome. Fragmentation spectra and peptides are represented as n-dimensional vectors, where n is given by the number of fragment ions considered, and the peptide mass. The identification score is given by the Euclidian distance between the spectra and the matching peptide in n-dimensional space. We show that this approach, using minimal information, allows for precise and fast peptide identification.Pubblicazioni consigliate
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