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Enhancing the quality of protein conformation ensembles with relative populations

Overview of attention for article published in Journal of Biomolecular NMR, February 2014
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Title
Enhancing the quality of protein conformation ensembles with relative populations
Published in
Journal of Biomolecular NMR, February 2014
DOI 10.1007/s10858-014-9818-2
Pubmed ID
Authors

Vijay Vammi, Tu-Liang Lin, Guang Song

Abstract

The function and dynamics of many proteins are best understood not from a single structure but from an ensemble. A high quality ensemble is necessary for accurately delineating protein dynamics. However, conformations in an ensemble are generally given equal weights. Few attempts were made to assign relative populations to the conformations, mainly due to the lack of right experimental data. Here we propose a method for assigning relative populations to ensembles using experimental residue dipolar couplings (RDC) as constraints, and show that relative populations can significantly enhance an ensemble's ability in representing the native states and dynamics. The method works by identifying conformation states within an ensemble and assigning appropriate relative populations to them. Each of these conformation states is represented by a sub-ensemble consisting of a subset of the conformations. Application to the ubiquitin X-ray ensemble clearly identifies two key conformation states, with relative populations in excellent agreement with previous work. We then apply the method to a reprotonated ERNST ensemble that is enhanced with a switched conformation, and show that as a result of population reweighting, not only the reproduction of RDCs is significantly improved, but common conformational features (particularly the dihedral angle distributions of ϕ 53 and ψ 52) also emerge for both the X-ray ensemble and the reprotonated ERNST ensemble.

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The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 48%
Student > Ph. D. Student 5 22%
Professor > Associate Professor 4 17%
Professor 1 4%
Unspecified 1 4%
Other 0 0%
Unknown 1 4%
Readers by discipline Count As %
Chemistry 7 30%
Agricultural and Biological Sciences 5 22%
Biochemistry, Genetics and Molecular Biology 3 13%
Computer Science 2 9%
Physics and Astronomy 2 9%
Other 1 4%
Unknown 3 13%
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 29 May 2014.
All research outputs
#15,298,293
of 22,751,628 outputs
Outputs from Journal of Biomolecular NMR
#382
of 615 outputs
Outputs of similar age
#192,939
of 313,182 outputs
Outputs of similar age from Journal of Biomolecular NMR
#2
of 4 outputs
Altmetric has tracked 22,751,628 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 615 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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