A novel protein identification framework, PILOT_PROTEIN, has been developed to construct a comprehensive list of all unmodified proteins that are present in a living sample. It uses the peptide identification results from the PILOT_SEQUEL algorithm to initially determine all unmodified proteins within the sample. Using a rigorous biclustering approach that groups incorrect peptide sequences with other homologous sequences, the number of false positives reported is minimized. A sequence tag proc
edure is then incorporated along with the untargeted PTM identification algorithm, PILOT_PTM, to determine a list of all modification types and sites for each protein. The unmodified protein identification algorithm, PILOT_PROTEIN, is compared to the methods SEQUEST, InsPecT, X!Tandem, VEMS, and ProteinProspector using both prepared protein samples and a more complex chromatin digest. The algorithm demonstrates superior protein identification accuracy with a lower false positive rate. All materials are freely available to the scientific community at
edu" class="extLink">http://pumpd.princeton.edu.
Keywords:
authors" href="http://pubs.acs.org/action/doSearch?action=search&searchText=tandem+mass+spectrometry&qsSearchArea=searchText">tandem mass spectrometry; authors" href="http://pubs.acs.org/action/doSearch?action=search&searchText=integer+linear+optimization&qsSearchArea=searchText">integer linear optimization; authors" href="http://pubs.acs.org/action/doSearch?action=search&searchText=post%5C-translational+modifications&qsSearchArea=searchText">post-translational modifications; authors" href="http://pubs.acs.org/action/doSearch?action=search&searchText=protein+identification&qsSearchArea=searchText">protein identification; authors" href="http://pubs.acs.org/action/doSearch?action=search&searchText=peptide+identification&qsSearchArea=searchText">peptide identification; authors" href="http://pubs.acs.org/action/doSearch?action=search&searchText=de+novo%2Fdatabase+search&qsSearchArea=searchText">de novo/database search