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Protein Scaffolds Can Enhance the Bistability of Multisite Phosphorylation Systems

Overview of attention for article published in PLoS Computational Biology, June 2012
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Title
Protein Scaffolds Can Enhance the Bistability of Multisite Phosphorylation Systems
Published in
PLoS Computational Biology, June 2012
DOI 10.1371/journal.pcbi.1002551
Pubmed ID
Authors

Carlo Chan, Xinfeng Liu, Liming Wang, Lee Bardwell, Qing Nie, Germán Enciso

Abstract

The phosphorylation of a substrate at multiple sites is a common protein modification that can give rise to important structural and electrostatic changes. Scaffold proteins can enhance protein phosphorylation by facilitating an interaction between a protein kinase enzyme and its target substrate. In this work we consider a simple mathematical model of a scaffold protein and show that under specific conditions, the presence of the scaffold can substantially raise the likelihood that the resulting system will exhibit bistable behavior. This phenomenon is especially pronounced when the enzymatic reactions have sufficiently large K(M), compared to the concentration of the target substrate. We also find for a closely related model that bistable systems tend to have a specific kinetic conformation. Using deficiency theory and other methods, we provide a number of necessary conditions for bistability, such as the presence of multiple phosphorylation sites and the dependence of the scaffold binding/unbinding rates on the number of phosphorylated sites.

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The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Australia 1 2%
Argentina 1 2%
Canada 1 2%
Japan 1 2%
Russia 1 2%
Unknown 47 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 35%
Student > Ph. D. Student 12 22%
Professor 6 11%
Student > Doctoral Student 4 7%
Student > Postgraduate 2 4%
Other 6 11%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 28%
Biochemistry, Genetics and Molecular Biology 12 22%
Mathematics 6 11%
Computer Science 4 7%
Physics and Astronomy 4 7%
Other 5 9%
Unknown 8 15%