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Multiscale molecular dynamics simulations of rotary motor proteins

Overview of attention for article published in Biophysical Reviews, December 2017
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Title
Multiscale molecular dynamics simulations of rotary motor proteins
Published in
Biophysical Reviews, December 2017
DOI 10.1007/s12551-017-0373-4
Pubmed ID
Authors

Toru Ekimoto, Mitsunori Ikeguchi

Abstract

Protein functions require specific structures frequently coupled with conformational changes. The scale of the structural dynamics of proteins spans from the atomic to the molecular level. Theoretically, all-atom molecular dynamics (MD) simulation is a powerful tool to investigate protein dynamics because the MD simulation is capable of capturing conformational changes obeying the intrinsically structural features. However, to study long-timescale dynamics, efficient sampling techniques and coarse-grained (CG) approaches coupled with all-atom MD simulations, termed multiscale MD simulations, are required to overcome the timescale limitation in all-atom MD simulations. Here, we review two examples of rotary motor proteins examined using free energy landscape (FEL) analysis and CG-MD simulations. In the FEL analysis, FEL is calculated as a function of reaction coordinates, and the long-timescale dynamics corresponding to conformational changes is described as transitions on the FEL surface. Another approach is the utilization of the CG model, in which the CG parameters are tuned using the fluctuation matching methodology with all-atom MD simulations. The long-timespan dynamics is then elucidated straightforwardly by using CG-MD simulations.

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Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Student > Master 4 20%
Professor 2 10%
Researcher 2 10%
Student > Bachelor 1 5%
Other 1 5%
Unknown 6 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 25%
Pharmacology, Toxicology and Pharmaceutical Science 2 10%
Agricultural and Biological Sciences 2 10%
Computer Science 1 5%
Physics and Astronomy 1 5%
Other 1 5%
Unknown 8 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 December 2017.
All research outputs
#20,454,971
of 23,011,300 outputs
Outputs from Biophysical Reviews
#704
of 799 outputs
Outputs of similar age
#374,467
of 439,400 outputs
Outputs of similar age from Biophysical Reviews
#31
of 49 outputs
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