Investigating MS2/MS3 Matching Statistics

Abstract

Improvements in ion trap instrumentation have made n-dimensional mass spectrometry more practical. The overall goal of the study was to describe a model for making use of MS2 and MS3 information in mass spectrometry experiments. We present a statistical model for adjusting peptide identification probabilities based on the combined information obtained by coupling peptide assignments of consecutive MS2 and MS3 spectra. Using two data sets, a mixture of known proteins and a complex phosphopeptide-enriched sample, we demonstrate an increase in discriminating power of the adjusted probabilities compared with models using MS2 or MS3 data only. This work also addresses the overall value of generating MS3 data as compared with an MS2-only approach with a focus on the analysis of phosphopeptide data.