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A Potent and Selective Peptide Blocker of the Kv1.3 Channel: Prediction from Free-Energy Simulations and Experimental Confirmation

Overview of attention for article published in PLoS ONE, November 2013
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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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
1 tweeter
patent
1 patent
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

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37 Dimensions

Readers on

mendeley
53 Mendeley
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Title
A Potent and Selective Peptide Blocker of the Kv1.3 Channel: Prediction from Free-Energy Simulations and Experimental Confirmation
Published in
PLoS ONE, November 2013
DOI 10.1371/journal.pone.0078712
Pubmed ID
Authors

M. Harunur Rashid, Germano Heinzelmann, Redwan Huq, Rajeev B. Tajhya, Shih Chieh Chang, Sandeep Chhabra, Michael W. Pennington, Christine Beeton, Raymond S. Norton, Serdar Kuyucak

Abstract

The voltage-gated potassium channel Kv1.3 is a well-established target for treatment of autoimmune diseases. ShK peptide from a sea anemone is one of the most potent blockers of Kv1.3 but its application as a therapeutic agent for autoimmune diseases is limited by its lack of selectivity against other Kv channels, in particular Kv1.1. Accurate models of Kv1.x-ShK complexes suggest that specific charge mutations on ShK could considerably enhance its specificity for Kv1.3. Here we evaluate the K18A mutation on ShK, and calculate the change in binding free energy associated with this mutation using the path-independent free energy perturbation and thermodynamic integration methods, with a novel implementation that avoids convergence problems. To check the accuracy of the results, the binding free energy differences were also determined from path-dependent potential of mean force calculations. The two methods yield consistent results for the K18A mutation in ShK and predict a 2 kcal/mol gain in Kv1.3/Kv1.1 selectivity free energy relative to wild-type peptide. Functional assays confirm the predicted selectivity gain for ShK[K18A] and suggest that it will be a valuable lead in the development of therapeutics for autoimmune diseases.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
United States 1 2%
France 1 2%
Australia 1 2%
Unknown 49 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 30%
Researcher 11 21%
Professor 6 11%
Student > Master 5 9%
Student > Bachelor 4 8%
Other 10 19%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 34%
Biochemistry, Genetics and Molecular Biology 12 23%
Physics and Astronomy 4 8%
Chemistry 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 3 6%
Other 8 15%
Unknown 5 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 09 June 2018.
All research outputs
#1,892,117
of 13,043,953 outputs
Outputs from PLoS ONE
#28,577
of 140,594 outputs
Outputs of similar age
#34,673
of 244,032 outputs
Outputs of similar age from PLoS ONE
#1,177
of 7,380 outputs
Altmetric has tracked 13,043,953 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 140,594 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one has done well, scoring higher than 79% 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 244,032 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 85% of its contemporaries.
We're also able to compare this research output to 7,380 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.