Verification of Single-Peptide Protein Identifications by the Application of Complementary Database Search Algorithms.

摘要

Protein identifications from complex biological mixtures often involve the application of tandem mass spectrometry techniques. One such technique, known as the Multi-Dimensional Protein Identification Technique, or MudPIT, involves the use of computer search algorithms that automate the process of identifying proteins present in the sample mixture based on mass spectrometry analysis. This technique involves digestion of the protein mixture with a protease such as trypsin, followed by liquid chromatography separation using first a strong cation exchange column followed by a reverse-phase separation. Peptides eluting from these separations are subjected to ionization and fragmentation in the mass spectrometer. The database search algorithms are then used to match the acquired spectra to peptide sequences from a protein database. These algorithms, while helpful, are far from perfect when it comes to accuracy of peptide identifications. These programs identify peptides by comparing the collected spectra to predicted spectra from the database sequences and applying a score to that identification. The peptide with the highest score is the one selected as the identification.