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Connecting the Kinetics and Energy Landscape of tRNA Translocation on the Ribosome

Overview of attention for article published in PLoS Computational Biology, March 2013
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Title
Connecting the Kinetics and Energy Landscape of tRNA Translocation on the Ribosome
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1003003
Pubmed ID
Authors

Paul C. Whitford, Scott C. Blanchard, Jamie H. D. Cate, Karissa Y. Sanbonmatsu

Abstract

Functional rearrangements in biomolecular assemblies result from diffusion across an underlying energy landscape. While bulk kinetic measurements rely on discrete state-like approximations to the energy landscape, single-molecule methods can project the free energy onto specific coordinates. With measures of the diffusion, one may establish a quantitative bridge between state-like kinetic measurements and the continuous energy landscape. We used an all-atom molecular dynamics simulation of the 70S ribosome (2.1 million atoms; 1.3 microseconds) to provide this bridge for specific conformational events associated with the process of tRNA translocation. Starting from a pre-translocation configuration, we identified sets of residues that collectively undergo rotary rearrangements implicated in ribosome function. Estimates of the diffusion coefficients along these collective coordinates for translocation were then used to interconvert between experimental rates and measures of the energy landscape. This analysis, in conjunction with previously reported experimental rates of translocation, provides an upper-bound estimate of the free-energy barriers associated with translocation. While this analysis was performed for a particular kinetic scheme of translocation, the quantitative framework is general and may be applied to energetic and kinetic descriptions that include any number of intermediates and transition states.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Germany 1 1%
Estonia 1 1%
Italy 1 1%
Japan 1 1%
Spain 1 1%
Unknown 82 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 33%
Researcher 20 22%
Professor > Associate Professor 8 9%
Student > Bachelor 6 7%
Professor 6 7%
Other 13 14%
Unknown 7 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 33%
Biochemistry, Genetics and Molecular Biology 19 21%
Chemistry 15 17%
Physics and Astronomy 12 13%
Computer Science 4 4%
Other 1 1%
Unknown 9 10%