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GroPBS: Fast Solver for Implicit Electrostatics of Biomolecules

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, November 2015
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Title
GroPBS: Fast Solver for Implicit Electrostatics of Biomolecules
Published in
Frontiers in Bioengineering and Biotechnology, November 2015
DOI 10.3389/fbioe.2015.00186
Pubmed ID
Authors

Franziska Bertelshofer, Liping Sun, Günther Greiner, Rainer A. Böckmann

Abstract

Knowledge about the electrostatic potential on the surface of biomolecules or biomembranes under physiological conditions is an important step in the attempt to characterize the physico-chemical properties of these molecules and, in particular, also their interactions with each other. Additionally, knowledge about solution electrostatics may also guide the design of molecules with specified properties. However, explicit water models come at a high computational cost, rendering them unsuitable for large design studies or for docking purposes. Implicit models with the water phase treated as a continuum require the numerical solution of the Poisson-Boltzmann equation (PBE). Here, we present a new flexible program for the numerical solution of the PBE, allowing for different geometries, and the explicit and implicit inclusion of membranes. It involves a discretization of space and the computation of the molecular surface. The PBE is solved using finite differences, the resulting set of equations is solved using a Gauss-Seidel method. It is shown for the example of the sucrose transporter ScrY that the implicit inclusion of a surrounding membrane has a strong effect also on the electrostatics within the pore region and, thus, needs to be carefully considered, e.g., in design studies on membrane proteins.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 33%
Student > Ph. D. Student 4 33%
Student > Bachelor 1 8%
Student > Master 1 8%
Professor > Associate Professor 1 8%
Other 0 0%
Unknown 1 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 50%
Chemistry 3 25%
Computer Science 1 8%
Mathematics 1 8%
Unknown 1 8%
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 17 November 2015.
All research outputs
#18,430,915
of 22,833,393 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,398
of 6,565 outputs
Outputs of similar age
#278,383
of 386,426 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#41
of 63 outputs
Altmetric has tracked 22,833,393 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 6,565 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 30th percentile – i.e., 30% 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 386,426 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 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.