A face in the crowd: recognizing peptides through database search

Abstract

Peptide identification via tandem mass spectrometry sequence database searching is a key method in the array of tools available to the proteomics researcher. The ability to rapidly and sensitively acquire tandem mass spectrometry data and perform peptide and protein identifications has become a commonly used proteomics analysis technique because of advances in both instrumentation and software. Although many different tandem mass spectrometry database search tools are currently available from both academic and commercial sources, these algorithms share similar core elements while maintaining distinctive features. This review revisits the mechanism of sequence database searching and discusses how various parameter settings impact the underlying search.

Fig. 1.

A snapshot of MS/MS data acquisition. A schematic showing the relationship between MS scans (blue) and MS/MS scans (red) in a typical tandem MS experiment. In this example, a precursor ion in each MS scan is isolated and fragmented, resulting in the MS/MS spectra that alternate every scan with the MS spectra. Typical data acquisition would acquire multiple MS/MS scans for each MS scan. In addition to the fragmentation pattern from each MS/MS spectrum used in a database search, the precursor ion's m/z, charge state, and mass accuracy of the measured precursor m/z are obtained from the MS spectrum.

Fig. 2.

Data acquisition and database search. For a given experimental MS/MS spectrum, protein sequences from a database are in silico digested and peptides of the right mass are selected. Theoretical fragment ions from each candidate peptide are calculated and used to generate a similarity or probability score by comparing the theoretical fragment ion masses against the experimental spectrum. Each candidate peptide is scored against the experimental spectrum and the best matching peptides and their scores are reported.