Computational prediction of proteotypic peptides for quantitative proteomics.
Nat Biotechnol
; 25(1): 125-31, 2007 Jan.
Article
em En
| MEDLINE
| ID: mdl-17195840
ABSTRACT
Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Although such analyses typically assume that a protein's peptide fragments are observed with equal likelihood, only a few so-called 'proteotypic' peptides are repeatedly and consistently identified for any given protein present in a mixture. Using >600,000 peptide identifications generated by four proteomic platforms, we empirically identified >16,000 proteotypic peptides for 4,030 distinct yeast proteins. Characteristic physicochemical properties of these peptides were used to develop a computational tool that can predict proteotypic peptides for any protein from any organism, for a given platform, with >85% cumulative accuracy. Possible applications of proteotypic peptides include validation of protein identifications, absolute quantification of proteins, annotation of coding sequences in genomes, and characterization of the physical principles governing key elements of mass spectrometric workflows (e.g., digestion, chromatography, ionization and fragmentation).
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Coleções:
01-internacional
Temas:
Geral
Base de dados:
MEDLINE
Assunto principal:
Peptídeos
/
Espectrometria de Massas
/
Algoritmos
/
Mapeamento de Peptídeos
/
Proteoma
/
Perfilação da Expressão Gênica
/
Análise de Sequência de Proteína
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Nat Biotechnol
Assunto da revista:
BIOTECNOLOGIA
Ano de publicação:
2007
Tipo de documento:
Article
País de afiliação:
Estados Unidos