Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification.

Here we present the theoretical and experimental evaluation of peptide isoelectric point as a method to aid in the identification of peptides from complex mixtures. Predicted pI values were found to match closely the experimentally obtained data, resulting in the development of a unique filter that lowers the effective false positive rate for peptide identification. Due to the reduction of the false positive rate, the cross-correlation parameters Xcorr and deltaCn from the SEQUEST program can be lowered resulting in 25% more peptide identifications. This approach was successfully applied to analysis of the soluble fraction of the E. coli proteome, where 417 proteins were identified from 1022 peptides using just 20 microg of material.