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On the Helix Propensity in Generalized Born Solvent Descriptions of Modeling the Dark Proteome

Overview of attention for article published in Frontiers in Molecular Biosciences, January 2017
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Title
On the Helix Propensity in Generalized Born Solvent Descriptions of Modeling the Dark Proteome
Published in
Frontiers in Molecular Biosciences, January 2017
DOI 10.3389/fmolb.2017.00003
Pubmed ID
Authors

Mark A. Olson

Abstract

Intrinsically disordered proteins that populate the so-called "Dark Proteome" offer challenging benchmarks of atomistic simulation methods to accurately model conformational transitions on a multidimensional energy landscape. This work explores the application of parallel tempering with implicit solvent models as a computational framework to capture the conformational ensemble of an intrinsically disordered peptide derived from the Ebola virus protein VP35. A recent X-ray crystallographic study reported a protein-peptide interface where the VP35 peptide underwent a folding transition from a disordered form to a helix-β-turn-helix topological fold upon molecular association with the Ebola protein NP. An assessment is provided of the accuracy of two generalized Born solvent models (GBMV2 and GBSW2) using the CHARMM force field and applied with temperature-based replica exchange dynamics to calculate the disorder propensity of the peptide and its probability density of states in a continuum solvent. A further comparison is presented of applying an explicit/implicit solvent hybrid replica exchange simulation of the peptide to determine the effect of modeling water interactions at the all-atom resolution.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 30%
Student > Ph. D. Student 2 20%
Professor 1 10%
Student > Doctoral Student 1 10%
Unknown 3 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 30%
Agricultural and Biological Sciences 2 20%
Physics and Astronomy 1 10%
Chemistry 1 10%
Unknown 3 30%
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 01 February 2017.
All research outputs
#17,870,599
of 22,950,943 outputs
Outputs from Frontiers in Molecular Biosciences
#1,691
of 3,827 outputs
Outputs of similar age
#293,471
of 420,210 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#12
of 20 outputs
Altmetric has tracked 22,950,943 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,827 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 420,210 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.