A probability-based approach for high-throughput protein phosphorylation analysis and site localization
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%.
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Correct assignment of phosphorylation within a peptide sequence was evaluated using the Ascore algorithm.
“Correct assignment of phosphorylation within a peptide sequence was evaluated using the Ascore algorithm90.”
From LKB1 regulates JNK-dependent stress signaling and apoptotic dependency of KRAS-mutant lung cancers (2025) · cites this paper as [90]
Confidently localized phosphorylation sites with an AScore greater than 13 were selected for analysis.
“confidently localized sites with a AScore > 13 were selected for analysis (p-value < 0.05)54.”
From Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease (2020) · cites this paper as [54]
The probability of correct phosphorylation site localization was assessed by the Ascore algorithm.
“The probability of correct phosphorylation site localization was assessed by the Ascore algorithm (24).”
From Identification of a Key Lysine Residue in Heat Shock Protein 90 Required for Azole and Echinocandin Resistance in Aspergillus fumigatus (2014) · cites this paper as [24]
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“Correct assignment of phosphorylation within a peptide sequence was evaluated using the Ascore algorithm 90 .”
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- Authors
- Beausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P.
- Affiliations
- Harvard University (US)
- Dartmouth Cancer Center (US)
- Corresponding author
- Gygi, Steven P
- Venue
- Nature Biotechnology
- Published
- 2006-09-10
- Volume
- 24
- Issue
- 10
- Pages
- 1285-1292
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W1993450321
- Cited by
- 1,577
- References
- 21
- Citations by year
- 2026: 44 · 2025: 58 · 2024: 74 · 2023: 81 · 2022: 64 · 2021: 81 · 2020: 78 · 2019: 71 · 2018: 75 · 2017: 80 · 2016: 68 · 2015: 99 · 2014: 118 · 2013: 100 · 2012: 112
- FWCI
- 31.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Human Genome Research Institute (HG03456, R01HG003456)
- National Institute of General Medical Sciences (GM 67945, R01GM067945)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- protein phosphorylation, phosphorylation site localization, false positive rate, HeLa cells
- MeSH terms
- Algorithms, HeLa Cells, Humans, Image Processing, Computer-Assisted, Peptide Mapping, Phosphorylation, Probability, Mass Spectrometry, Nocodazole
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