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Related Concept Videos

Phosphorylation01:02

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The addition or removal of phosphate groups from proteins is the most common chemical modification that regulates cellular processes. These modifications can affect the structure, activity, stability, and localization of proteins within cells as well as their interactions with other proteins.
During phosphorylation, protein kinases transfer the terminal phosphate group of ATP to specific amino acid side chains of substrate proteins. Serine, threonine, and tyrosine are the most commonly...
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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.
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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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PhosR enables processing and functional analysis of phosphoproteomic data.

Hani Jieun Kim1, Taiyun Kim1, Nolan J Hoffman2

  • 1School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia; Computational Systems Biology Group, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.

Cell Reports
|February 24, 2021
PubMed
Summary

PhosR, an R package suite, enhances phosphoproteomic data analysis for inferring kinase and signaling pathway activity. It enables robust data processing and biological knowledge discovery from mass spectrometry-based studies.

Keywords:
batch correctionimputationkinase-substrate predictionmass spectrometrynormalisationphosphoproteomicssignalling networkssignalomesstably phosphorylated sites

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Area of Science:

  • Biochemistry
  • Systems Biology
  • Bioinformatics

Background:

  • Mass spectrometry (MS)-based phosphoproteomics offers global profiling of cellular signaling.
  • Understanding kinase and signaling pathway actions is crucial for interpreting phosphoproteomic data.

Purpose of the Study:

  • To present PhosR, a suite of R packages for comprehensive phosphoproteomic data analysis.
  • To enable inference of active kinases and signaling pathways from phosphoproteomic datasets.

Main Methods:

  • Development of R packages for phosphoproteomic data analysis.
  • Application of PhosR for data imputation and normalization using stably phosphorylated sites.
  • Implementation of functional analysis for kinase and pathway inference.
  • Introduction of a 'signalome' construction method for visualizing kinase interactions.

Main Results:

  • PhosR effectively performs data imputation and normalization.
  • The tool facilitates functional analysis to identify active kinases and signaling pathways.
  • The 'signalome' method provides a novel way to summarize kinase interactions and signal transduction.

Conclusions:

  • PhosR is a valuable tool for processing and extracting biological knowledge from MS-based phosphoproteomic data.
  • The developed methodologies enhance the interpretation of complex signaling networks.