RESUMO
In high-throughput proteomics, the bottom-up approach has become a widely used method for the identification of proteins that is based on tryptic peptide MS/MS analysis. Separation methodologies that use IEF of tryptic peptides have recently been introduced and provide an extra dimension of peptide separation. In addition to its great fractionation capability, tryptic peptide prefractionation by IEF can also increase the protein identification success. The pI information of the peptide gained can be successfully used in a post-database search filtering step. We introduce a filtering algorithm that is based on the comparison of the experimental and theoretical pI's to validate peptide identifications by MS/MS data search engines.
Assuntos
Algoritmos , Biologia Computacional/métodos , Armazenamento e Recuperação da Informação/métodos , Proteínas/química , Espectrometria de Massas em Tandem , Bases de Dados de Proteínas , Hidrólise , Focalização Isoelétrica , Ponto Isoelétrico , Peptídeos/química , Proteômica/métodos , Software , Validação de Programas de Computador , TripsinaRESUMO
The identification of disease markers in tissues and body fluids requires an extensive and thorough analysis of its protein constituents. In our efforts to identify biomarkers for affective and neurological disorders we are pursuing several different strategies. On one hand we are using animal models that represent defined phenotypes characteristic for the respective disorder in humans. In addition, we are analyzing human specimens from carefully phenotyped patient groups. Several fractions representing different protein classes from human cerebrospinal fluid obtained by lumbar puncture are used for this purpose. Our biomarker identification efforts range from classical proteomics approaches such as two dimensional gel electrophoresis and mass spectrometry to phage display screens with cerebrospinal fluid antibodies.
