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Initiating a watch list for Ebola virus antibody escape mutations

Overview of attention for article published in PeerJ, February 2016
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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blogs
1 blog
twitter
6 X users
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1 patent
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1 Facebook page

Readers on

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45 Mendeley
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Article details
Title
Initiating a watch list for Ebola virus antibody escape mutations
Published in
PeerJ, February 2016
DOI 10.7717/peerj.1674
Pubmed ID
Authors
Abstract

The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest in recorded history and resulted in over 11,000 deaths. It is essential that strategies for treatment and containment be developed to avoid future epidemics of this magnitude. With the development of vaccines and antibody-based therapies using the envelope glycoprotein (GP) of the 1976 Mayinga strain, one important strategy is to anticipate how the evolution of EBOV might compromise these efforts. In this study we have initiated a watch list of potential antibody escape mutations of EBOV by modeling interactions between GP and the antibody KZ52. The watch list was generated using molecular modeling to estimate stability changes due to mutation. Every possible mutation of GP was considered and the list was generated from those that are predicted to disrupt GP-KZ52 binding but not to disrupt the ability of GP to fold and to form trimers. The resulting watch list contains 34 mutations (one of which has already been seen in humans) at six sites in the GP2 subunit. Should mutations from the watch list appear and spread during an epidemic, it warrants attention as these mutations may reflect an evolutionary response from the virus that could reduce the effectiveness of interventions such as vaccination. However, this watch list is incomplete and emphasizes the need for more experimental structures of EBOV interacting with antibodies in order to expand the watch list to other epitopes. We hope that this work provokes experimental research on evolutionary escape in both Ebola and other viral pathogens.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 7 16%
Student > Ph. D. Student 7 16%
Researcher 6 13%
Librarian 4 9%
Other 4 9%
Other 5 11%
Unknown 12 27%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 22%
Medicine and Dentistry 5 11%
Nursing and Health Professions 4 9%
Immunology and Microbiology 3 7%
Engineering 3 7%
Other 6 13%
Unknown 14 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 10 December 2024.
All research outputs
#3,007,723
of 31,439,095 outputs
Outputs from PeerJ
#2,629
of 16,226 outputs
Outputs of similar age
#37,466
of 323,350 outputs
Outputs of similar age from PeerJ
#66
of 353 outputs
Altmetric has tracked 31,439,095 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,226 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has done well, scoring higher than 83% 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 323,350 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 88% of its contemporaries.
We're also able to compare this research output to 353 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.