A Probability-Based Approach for High-Throughput Protein Phosphorylation Analysis and Site Localization

Nat Biotechnol. 2006 Oct;24(10):1285-92. doi: 10.1038/nbt1240. Epub 2006 Sep 10.

Abstract

Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • HeLa Cells / drug effects
  • Humans
  • Image Processing, Computer-Assisted
  • Mass Spectrometry / methods*
  • Nocodazole / pharmacology
  • Peptide Mapping / methods*
  • Phosphorylation
  • Probability

Substances

  • Nocodazole