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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%. [ABSTRACT FROM AUTHOR]

Tyrosine kinases play a prominent role in human cancer, yet the oncogenic signaling pathways driving cell proliferation and survival have been difficult to identify, in part because of the complexity of the pathways and in part because of low cellular levels of tyrosine phosphorylation. In general, global phosphoproteomic approaches reveal small numbers of peptides containing phosphotyrosine. We have developed a strategy that emphasizes the phosphotyrosine component of the phosphoproteome and identifies large numbers of tyrosine phosphorylation sites. Peptides containing phosphotyrosine are isolated directly from protease-digested cellular protein extracts with a phosphotyrosine-specific antibody and are identified by tandem mass spectrometry. Applying this approach to several cell systems, including cancer cell lines, shows it can be used to identify activated protein kinases and their phosphorylated substrates without prior knowledge of the signaling networks that are activated, a first step in profiling normal and oncogenic signaling networks. [ABSTRACT FROM AUTHOR]