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Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, September 2015
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Title
Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review
Published in
Frontiers in Bioengineering and Biotechnology, September 2015
DOI 10.3389/fbioe.2015.00125
Pubmed ID
Authors

Fujisaki, Hiroshi, Moritsugu, Kei, Matsunaga, Yasuhiro, Morishita, Tetsuya, Maragliano, Luca

Abstract

Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 5%
Czechia 1 2%
Unknown 40 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 28%
Student > Ph. D. Student 10 23%
Student > Bachelor 5 12%
Professor > Associate Professor 4 9%
Professor 3 7%
Other 5 12%
Unknown 4 9%
Readers by discipline Count As %
Chemistry 6 14%
Physics and Astronomy 6 14%
Agricultural and Biological Sciences 6 14%
Chemical Engineering 5 12%
Engineering 4 9%
Other 8 19%
Unknown 8 19%
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 03 September 2015.
All research outputs
#18,425,370
of 22,826,360 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,396
of 6,549 outputs
Outputs of similar age
#192,520
of 266,946 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#40
of 59 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,549 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.