Prediction of missed proteolytic cleavages for the selection of surrogate peptides for quantitative proteomics.

ABSTRACT: Quantitative proteomics experiments are usually performed using proteolytic peptides as surrogates for their parent proteins, inferring protein amounts from peptide-level quantitation. This process is frequently dependent on complete digestion of the parent protein to its limit peptides so that their signal is truly representative. Unfortunately, proteolysis is often incomplete, and missed cleavage peptides are frequently produced that are unlikely to be optimal surrogates for quantitation, particularly for label-mediated approaches seeking to derive absolute values. We have generated a predictive computational tool that is able to predict which candidate proteolytic peptide bonds are likely to be missed by the standard enzyme trypsin. Our cross-validated prediction tool uses support vecto

SUBMITTER: Lawless C 

PROVIDER: S-EPMC3437044 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature