IDSieve: Protein Identification Using Peptide pI Filtering of MS/MS Data for Improved Confidence in Identifications.

The main challenge of tandem mass spectrometry based proteomic analysis is to correctly match the tandem mass spectra produced to the correct peptides. However, the large number of protein sequences in a database increases the chances of a false positive identification for any given peptide match. Here we present an automated algorithm called IDSieve that utilizes target-decoy database search strategy in combination with pI filtering to allow greater confidence for peptide identifications. IDSieve considers the SEQUEST parameters Xcorr and aCn to assign statistical confidence (false discovery rates) to the peptide matches. The distribution of predicted pI values for peptide spectrum matches (PSMs) is considered separately for each immobilized pH gradient isoelectric focusing fraction, and matches with pI values within 1.5 times inter-quartile range (within pI range) are analyzed independently of matches outside the pI ranges. We tested the performance of IDSieve and Peptide/Protein Prophet on the SEQUEST outputs from 60 immobilized pH gradient isoelectric focusing fractions derived from mouse intestinal epithelial cell protein extracts. Our results demonstrated that IDSieve produced 1355 more peptide spectrum matches (or 330 more peptides) than Peptide Prophet using comparable false positive rate cutoffs. Therefore, combining pI filtering with the appropriate statistical significance measurements allows for a higher number of protein identifications without adversely affecting the false positive rate. We further tested the performance of pI filtering using ID Sieve when samples were prefractionated using either pH range 3.5–4.5 or 3–10, and either 24cm or 7cm IPG strips.