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Dual Coordination of Post Translational Modifications in Human Protein Networks

Overview of attention for article published in PLoS Computational Biology, March 2013
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Title
Dual Coordination of Post Translational Modifications in Human Protein Networks
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002933
Pubmed ID
Authors

Jonathan Woodsmith, Atanas Kamburov, Ulrich Stelzl

Abstract

Post-translational modifications (PTMs) regulate protein activity, stability and interaction profiles and are critical for cellular functioning. Further regulation is gained through PTM interplay whereby modifications modulate the occurrence of other PTMs or act in combination. Integration of global acetylation, ubiquitination and tyrosine or serine/threonine phosphorylation datasets with protein interaction data identified hundreds of protein complexes that selectively accumulate each PTM, indicating coordinated targeting of specific molecular functions. A second layer of PTM coordination exists in these complexes, mediated by PTM integration (PTMi) spots. PTMi spots represent very dense modification patterns in disordered protein regions and showed an equally high mutation rate as functional protein domains in cancer, inferring equivocal importance for cellular functioning. Systematic PTMi spot identification highlighted more than 300 candidate proteins for combinatorial PTM regulation. This study reveals two global PTM coordination mechanisms and emphasizes dataset integration as requisite in proteomic PTM studies to better predict modification impact on cellular signaling.

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The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 2 2%
Austria 1 <1%
India 1 <1%
Denmark 1 <1%
Canada 1 <1%
Unknown 98 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 30%
Researcher 23 21%
Student > Master 14 13%
Student > Bachelor 8 7%
Professor > Associate Professor 6 6%
Other 10 9%
Unknown 14 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 36%
Biochemistry, Genetics and Molecular Biology 27 25%
Computer Science 6 6%
Medicine and Dentistry 6 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Other 12 11%
Unknown 14 13%