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Web-Based Computational Chemistry Education with CHARMMing III: Reduction Potentials of Electron Transfer Proteins

Overview of attention for article published in PLoS Computational Biology, July 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

blogs
1 blog
twitter
3 X users
googleplus
1 Google+ user

Citations

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10 Dimensions

Readers on

mendeley
57 Mendeley
citeulike
1 CiteULike
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Title
Web-Based Computational Chemistry Education with CHARMMing III: Reduction Potentials of Electron Transfer Proteins
Published in
PLoS Computational Biology, July 2014
DOI 10.1371/journal.pcbi.1003739
Pubmed ID
Authors

B. Scott Perrin, Benjamin T. Miller, Vinushka Schalk, H. Lee Woodcock, Bernard R. Brooks, Toshiko Ichiye

Abstract

A module for fast determination of reduction potentials, E°, of redox-active proteins has been implemented in the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org). The free energy of reduction, which is proportional to E°, is composed of an intrinsic contribution due to the redox site and an environmental contribution due to the protein and solvent. Here, the intrinsic contribution is selected from a library of pre-calculated density functional theory values for each type of redox site and redox couple, while the environmental contribution is calculated from a crystal structure of the protein using Poisson-Boltzmann continuum electrostatics. An accompanying lesson demonstrates a calculation of E°. In this lesson, an ionizable residue in a [4Fe-4S]-protein that causes a pH-dependent E° is identified, and the E° of a mutant that would test the identification is predicted. This demonstration is valuable to both computational chemistry students and researchers interested in predicting sequence determinants of E° for mutagenesis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Hungary 1 2%
United Kingdom 1 2%
Czechia 1 2%
Canada 1 2%
Ukraine 1 2%
Unknown 49 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 30%
Student > Ph. D. Student 11 19%
Professor 7 12%
Professor > Associate Professor 5 9%
Student > Bachelor 4 7%
Other 8 14%
Unknown 5 9%
Readers by discipline Count As %
Chemistry 20 35%
Biochemistry, Genetics and Molecular Biology 11 19%
Agricultural and Biological Sciences 9 16%
Physics and Astronomy 4 7%
Medicine and Dentistry 2 4%
Other 5 9%
Unknown 6 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 07 August 2014.
All research outputs
#3,307,024
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#2,910
of 8,960 outputs
Outputs of similar age
#31,939
of 240,094 outputs
Outputs of similar age from PLoS Computational Biology
#41
of 166 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 67% of its peers.
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 240,094 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 166 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.