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Biophysical Mechanism for Ras-Nanocluster Formation and Signaling in Plasma Membrane

Overview of attention for article published in PLOS ONE, July 2009
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Title
Biophysical Mechanism for Ras-Nanocluster Formation and Signaling in Plasma Membrane
Published in
PLOS ONE, July 2009
DOI 10.1371/journal.pone.0006148
Pubmed ID
Authors

Thomas Gurry, Ozan Kahramanoğulları, Robert G. Endres

Abstract

Ras GTPases are lipid-anchored G proteins, which play a fundamental role in cell signaling processes. Electron micrographs of immunogold-labeled Ras have shown that membrane-bound Ras molecules segregate into nanocluster domains. Several models have been developed in attempts to obtain quantitative descriptions of nanocluster formation, but all have relied on assumptions such as a constant, expression-level independent ratio of Ras in clusters to Ras monomers (cluster/monomer ratio). However, this assumption is inconsistent with the law of mass action. Here, we present a biophysical model of Ras clustering based on short-range attraction and long-range repulsion between Ras molecules in the membrane. To test this model, we performed Monte Carlo simulations and compared statistical clustering properties with experimental data. We find that we can recover the experimentally-observed clustering across a range of Ras expression levels, without assuming a constant cluster/monomer ratio or the existence of lipid rafts. In addition, our model makes predictions about the signaling properties of Ras nanoclusters in support of the idea that Ras nanoclusters act as an analog-digital-analog converter for high fidelity signaling.

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The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 9%
Czechia 1 3%
Germany 1 3%
Unknown 27 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 34%
Researcher 9 28%
Professor > Associate Professor 5 16%
Student > Master 3 9%
Lecturer 1 3%
Other 2 6%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 34%
Biochemistry, Genetics and Molecular Biology 9 28%
Physics and Astronomy 5 16%
Chemistry 2 6%
Immunology and Microbiology 1 3%
Other 1 3%
Unknown 3 9%