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Transmembrane Helix Dynamics of Bacterial Chemoreceptors Supports a Piston Model of Signalling

Overview of attention for article published in PLoS Computational Biology, October 2011
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Title
Transmembrane Helix Dynamics of Bacterial Chemoreceptors Supports a Piston Model of Signalling
Published in
PLoS Computational Biology, October 2011
DOI 10.1371/journal.pcbi.1002204
Pubmed ID
Authors

Benjamin A. Hall, Judith P. Armitage, Mark S. P. Sansom

Abstract

Transmembrane α-helices play a key role in many receptors, transmitting a signal from one side to the other of the lipid bilayer membrane. Bacterial chemoreceptors are one of the best studied such systems, with a wealth of biophysical and mutational data indicating a key role for the TM2 helix in signalling. In particular, aromatic (Trp and Tyr) and basic (Arg) residues help to lock α-helices into a membrane. Mutants in TM2 of E. coli Tar and related chemoreceptors involving these residues implicate changes in helix location and/or orientation in signalling. We have investigated the detailed structural basis of this via high throughput coarse-grained molecular dynamics (CG-MD) of Tar TM2 and its mutants in lipid bilayers. We focus on the position (shift) and orientation (tilt, rotation) of TM2 relative to the bilayer and how these are perturbed in mutants relative to the wildtype. The simulations reveal a clear correlation between small (ca. 1.5 Å) shift in position of TM2 along the bilayer normal and downstream changes in signalling activity. Weaker correlations are seen with helix tilt, and little/none between signalling and helix twist. This analysis of relatively subtle changes was only possible because the high throughput simulation method allowed us to run large (n = 100) ensembles for substantial numbers of different helix sequences, amounting to ca. 2000 simulations in total. Overall, this analysis supports a swinging-piston model of transmembrane signalling by Tar and related chemoreceptors.

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Geographical breakdown

Country Count As %
United Kingdom 6 8%
United States 4 5%
Germany 2 3%
Sweden 1 1%
Denmark 1 1%
Vietnam 1 1%
Unknown 61 80%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 36%
Researcher 17 22%
Student > Master 7 9%
Student > Doctoral Student 4 5%
Professor > Associate Professor 4 5%
Other 10 13%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 36%
Chemistry 15 20%
Biochemistry, Genetics and Molecular Biology 13 17%
Physics and Astronomy 6 8%
Engineering 2 3%
Other 8 11%
Unknown 5 7%