Ascore: Taking on matching of Phosphorylated Peptides

A probability-based approach for high-throughput protein phosphorylation analysis and site localization Sean A Beausoleil, Judit Villen, Scott A Gerber, John Rush & Steven P Gygi

Search algorithms like SEQUEST or Mascot often identify the proper peptide sequence, but fail to provide information about the presence or absence of site-determining ions. As a result, users must manually inspect each spectrum to confirm proper site localization. The authors present a method named Ascore. Ascore works with results of matching techniques like SEQUEST to calculates phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra.
The Ascore method was able to match with 99% certainty two- to fourfold more phosphorylation sites in a data set of known phoshorylation sites than Sequest or Mascot.

This paper not only offers a novel technique for identifying phosphorylated peptides, but also provides data and a formula for the optimization of SEQUEST and Mascot for the analysis of phosphorylated peptides.

This paper is well written and organized. The authors build a very sound argument by first testing the assumptions of their quality measurement. I also appreciate that they looked at both sensitivity and precision. Many peptide identification methods are touted for their sensitivity while neglecting their precision.

A website that spectra and .out files can be submitted for Ascore analysis is under construction (http://Ascore.med.harvard.edu).