Prediction of missed cleavage sites in tryptic peptides aids protein identification in proteomics.

ABSTRACT: Protein identification via peptide mass fingerprinting (PMF) remains a key component of high-throughput proteomics experiments in post-genomic science. Candidate protein identifications are made using bioinformatic tools from peptide peak lists obtained via mass spectrometry (MS). These algorithms rely on several search parameters, including the number of potential uncut peptide bonds matching the primary specificity of the hydrolytic enzyme used in the experiment. Typically, up to one of these "missed cleavages" are considered by the bioinformatics search tools, usually after digestion of the in silico proteome by trypsin. Using two distinct, nonredundant datasets of peptides identified via PMF and tandem MS, a simple predictive method based on information theory is presented which is abl

SUBMITTER: Siepen JA 

PROVIDER: S-EPMC2664920 | biostudies-literature | 2007 Jan

REPOSITORIES: biostudies-literature