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Related Concept Videos

Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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A probability-based approach for high-throughput protein phosphorylation analysis and site localization.

Sean A Beausoleil1, Judit Villén, Scott A Gerber

  • 1Department of Cell Biology, Harvard Medical School, 240 Longwood Ave., Boston, Massachusetts 02115, USA.

Nature Biotechnology
|September 12, 2006
PubMed
Summary

This study introduces automated methods to improve protein phosphorylation site identification using mass spectrometry. These techniques enhance data accuracy, sensitivity, and localization, overcoming manual validation challenges in large-scale proteomics.

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Last Updated: Jul 20, 2026

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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Oligopeptide Competition Assay for Phosphorylation Site Determination
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Published on: May 18, 2017

Identification of Cyclin-dependent Kinase 1 Specific Phosphorylation Sites by an In Vitro Kinase Assay
12:26

Identification of Cyclin-dependent Kinase 1 Specific Phosphorylation Sites by an In Vitro Kinase Assay

Published on: May 3, 2018

Area of Science:

  • Proteomics
  • Biochemistry
  • Computational Biology

Background:

  • Identifying protein phosphorylation sites via LC-MS/MS presents significant data analysis challenges.
  • Manual validation of phosphorylation data is time-consuming and labor-intensive.

Purpose of the Study:

  • To develop automated methods for accurate and sensitive identification of protein phosphorylation sites.
  • To address challenges in data set error, sensitivity, and site localization in large-scale proteomics.

Main Methods:

  • Utilized the target-decoy approach to determine data set error rates.
  • Implemented a strategy to enhance data set sensitivity by filtering incorrect peptide spectral matches (PSMs).
  • Developed the Ascore, a probability-based metric for assessing phosphorylation site localization accuracy.

Main Results:

  • Generated a large-scale phosphorylation data set with a measured error rate.
  • Successfully identified 1,761 nonredundant phosphorylation sites from 491 proteins.
  • Achieved a peptide false-positive rate of 1.3% using automated methods.

Conclusions:

  • The developed automated methods effectively address key challenges in large-scale phosphoproteomics.
  • The Ascore provides a reliable measure for phosphorylation site localization.
  • This approach significantly advances the efficiency and accuracy of identifying phosphorylation sites.