Office of Technology Development (OTD)

Brian Halligan, PhD

One- and two-dimensional gels combined with mass spectrometry (MS) and LCMS have allowed the generation of large volumes of MS data that contain information to identify proteins, post-translational modifications thereof, and the members of protein-protein complexes. Currently, there are several ways to use MS data to identify peptides. One widely used approach is to match the experimental peptide spectra produced by collision induced disassociation (CID) with calculated theoretical spectra of every peptide in a database, such as done by Sequest. Mascot, Profound, and Protein Prospector use a somewhat different approach.

The major drawback of the approaches used by Sequest, Mascot, Profound, Protein Prospector, and similar programs is that they are geared to matching the data pair-wise from a single protein to every protein in a database. This is computationally time consuming and expensive.

The present invention relates to a method for correlating a query peptide to a predicted peptide in a predicted peptide database wherein the query peptide is obtained by cleaving a protein with one or more cleaving agents having defined cleavage specificity so that the cleavage products can be predicted and wherein the predicted peptide database comprises peptides predicted to be generated if said one or more cleaving agents are used to cleave one, two or more pre-selected amino acid sequences. The predicted peptide database is generated prior to and independent of any mass spectrum data acquisition for a particular analysis and the predicted peptide database can thus be pre-computed, reused, and distributed.

• Rapid protein and peptide identification
• Inexpensive method compared to those available
• Method and software driven, no change to hardware

Software and feasibility studies complete