Shotgun proteomics refers to the use of bottom-up proteomics techniques in which the protein content in a biological sample mixture is digested prior to separation and mass spectrometry analysis. Typically, liquid chromatography (LC) is coupled with tandem mass spectrometry (MS/MS) resulting in high-throughput peptide analysis. The MS/MS spectra are searched against a protein database to identify peptides in the sample. Currently, Sequest and Mascot are the most frequently used computer programs for conducting peptide identification, both comparing experimental MS/MS spectra with in silico spectra generated from the peptide sequences in a database. Compared to top-down proteomics techniques, shotgun proteomics avoids the modest separation efficiency and poor mass spectral sensitivity associated with intact protein analysis, but it also encounters a new problem in data analysis, that of determining the set of proteins present in the sample based on the peptide identification results.

At a first glance, this problem seems trivial. It may be concluded that a protein is present in the sample, if and only if at least one of its peptides is identified. This conclusion is true, however, only when each identified peptide is unique, i.e. when it belongs to only one protein. If some peptides are degenerate, i.e. shared by two or more proteins in the database, determining which of these proteins exist in the sample has multiple possible solutions. Indeed, tryptic peptides are frequently degenerate, especially for the proteome samples of vertebrates, which, due to recent gene duplications, often have a large number of paralogs. In addition, alternative splicing in higher eukaryotes results in many identical protein subsequences. The following example illustrates the extent of peptide degeneracy in a real proteomics experiment. Of the 693 identified peptides from a real rat sample used in this study (see sections 3-4 for details), 296 were unique and 397 were degenerate, when searched against the full proteome of R. norvegicus. These peptides can be assigned to a total of 805 proteins, of which only 149 proteins could be assigned based on the 296 unique peptides.