title: Improving Peptide identification using empirical scoring systems.
abstract: Peptides and proteins are routinely identified from peptide fragmentation spectra acquired in a mass spectrometer, analyzed by database search engines. The types of fragments that can be formed are known, and it is also well appreciated that certain fragment types are more common or more informative than others. However, most search engines do not use detailed knowledge of peptide fragmentation, but rather consider a limited range of fragments, giving each an equivalent weighting in their scoring system that decides which results are likely to be correct. This chapter discusses efforts to make use of information about the frequency of observation of different fragment ion types in order to produce more sophisticated and sensitive scoring systems and demonstrates how these new scoring systems are particularly powerful for analysis of electron capture or electron transfer dissociation data.
authors.affiliation: Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Chalkley
mesh_terms: D030562:Databases, Protein; D004579:Electron Transport; D013058:Mass Spectrometry / Q000379:methods*; D010446:Peptide Fragments / Q000032:analysis*; D057386:Search Engine
chemical_list: D010446:Peptide Fragments