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Insertion of the Ca2+-Independent Phospholipase A2 into a Phospholipid Bilayer via Coarse-Grained and Atomistic Molecular Dynamics Simulations

Overview of attention for article published in PLoS Computational Biology, July 2013
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Title
Insertion of the Ca2+-Independent Phospholipase A2 into a Phospholipid Bilayer via Coarse-Grained and Atomistic Molecular Dynamics Simulations
Published in
PLoS Computational Biology, July 2013
DOI 10.1371/journal.pcbi.1003156
Pubmed ID
Authors

Denis Bucher, Yuan-Hao Hsu, Varnavas D. Mouchlis, Edward A. Dennis, J. Andrew McCammon

Abstract

Group VI Ca²⁺-independent phospholipase A₂ (iPLA₂) is a water-soluble enzyme that is active when associated with phospholipid membranes. Despite its clear pharmaceutical relevance, no X-ray or NMR structural information is currently available for the iPLA₂ or its membrane complex. In this paper, we combine homology modeling with coarse-grained (CG) and all-atom (AA) molecular dynamics (MD) simulations to build structural models of iPLA₂ in association with a phospholipid bilayer. CG-MD simulations of the membrane insertion process were employed to provide a starting point for an atomistic description. Six AA-MD simulations were then conducted for 60 ns, starting from different initial CG structures, to refine the membrane complex. The resulting structures are shown to be consistent with each other and with deuterium exchange mass spectrometry (DXMS) experiments, suggesting that our approach is suitable for the modeling of iPLA₂ at the membrane surface. The models show that an anchoring region (residues 710-724) forms an amphipathic helix that is stabilized by the membrane. In future studies, the proposed iPLA₂ models should provide a structural basis for understanding the mechanisms of lipid extraction and drug-inhibition. In addition, the dual-resolution approach discussed here should provide the means for the future exploration of the impact of lipid diversity and sequence mutations on the activity of iPLA₂ and related enzymes.

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Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 6%
United Kingdom 1 2%
Czechia 1 2%
Russia 1 2%
Canada 1 2%
Unknown 44 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 25%
Researcher 12 24%
Student > Doctoral Student 5 10%
Professor 4 8%
Professor > Associate Professor 3 6%
Other 7 14%
Unknown 7 14%
Readers by discipline Count As %
Chemistry 14 27%
Agricultural and Biological Sciences 13 25%
Biochemistry, Genetics and Molecular Biology 9 18%
Chemical Engineering 1 2%
Environmental Science 1 2%
Other 3 6%
Unknown 10 20%
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 13 August 2013.
All research outputs
#22,778,604
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#8,570
of 8,964 outputs
Outputs of similar age
#187,148
of 210,055 outputs
Outputs of similar age from PLoS Computational Biology
#99
of 107 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 107 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.