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Inhibitors of the integrase–transportin-SR2 interaction block HIV nuclear import

Overview of attention for article published in Retrovirology, January 2018
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 tweeters

Citations

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5 Dimensions

Readers on

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22 Mendeley
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Title
Inhibitors of the integrase–transportin-SR2 interaction block HIV nuclear import
Published in
Retrovirology, January 2018
DOI 10.1186/s12977-018-0389-2
Pubmed ID
Authors

Jonas Demeulemeester, Jolien Blokken, Stéphanie De Houwer, Lieve Dirix, Hugo Klaassen, Arnaud Marchand, Patrick Chaltin, Frauke Christ, Zeger Debyser

Abstract

Combination antiretroviral therapy efficiently suppresses HIV replication in infected patients, transforming HIV/AIDS into a chronic disease. Viral resistance does develop however, especially under suboptimal treatment conditions such as poor adherence. As a consequence, continued exploration of novel targets is paramount to identify novel antivirals that do not suffer from cross-resistance with existing drugs. One new promising class of targets are HIV protein-cofactor interactions. Transportin-SR2 (TRN-SR2) is a β-karyopherin that was recently identified as an HIV-1 cofactor. It has been implicated in nuclear import of the viral pre-integration complex and was confirmed as a direct binding partner of HIV-1 integrase (IN). Nevertheless, consensus on its mechanism of action is yet to be reached. Here we describe the development and use of an AlphaScreen-based high-throughput screening cascade for small molecule inhibitors of the HIV-1 IN-TRN-SR2 interaction. False positives and nonspecific protein-protein interaction inhibitors were eliminated through different counterscreens. We identified and confirmed 2 active compound series from an initial screen of 25,608 small molecules. These compounds significantly reduced nuclear import of fluorescently labeled HIV particles. Alphascreen-based high-throughput screening can allow the identification of compounds representing a novel class of HIV inhibitors. These results corroborate the role of the IN-TRN-SR2 interaction in nuclear import. These compounds represent the first in class small molecule inhibitors of HIV-1 nuclear import.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 32%
Student > Master 3 14%
Other 2 9%
Student > Ph. D. Student 2 9%
Student > Doctoral Student 1 5%
Other 3 14%
Unknown 4 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 32%
Medicine and Dentistry 4 18%
Arts and Humanities 2 9%
Agricultural and Biological Sciences 1 5%
Immunology and Microbiology 1 5%
Other 1 5%
Unknown 6 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 January 2018.
All research outputs
#6,721,167
of 12,400,381 outputs
Outputs from Retrovirology
#328
of 618 outputs
Outputs of similar age
#151,386
of 357,412 outputs
Outputs of similar age from Retrovirology
#13
of 25 outputs
Altmetric has tracked 12,400,381 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 618 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 44th percentile – i.e., 44% 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 357,412 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.