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Dynamics of human protein kinase Aurora A linked to drug selectivity

Overview of attention for article published in eLife, June 2018
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)

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Article details
Title
Dynamics of human protein kinase Aurora A linked to drug selectivity
Published in
eLife, June 2018
DOI 10.7554/elife.36656
Pubmed ID
Authors
Abstract

Protein kinases are major drug targets, but the development of highly-selective inhibitors has been challenging due to the similarity of their active sites. The observation of distinct structural states of the fully-conserved Asp-Phe-Gly (DFG) loop has put the concept of conformational selection for the DFG-state at the center of kinase drug discovery. Recently, it was shown that Gleevec selectivity for the Tyr-kinases Abl was instead rooted in conformational changes after drug binding. Here, we investigate whether protein dynamics after binding is a more general paradigm for drug selectivity by characterizing the binding of several approved drugs to the Ser/Thr-kinase Aurora A. Using a combination of biophysical techniques, we propose a universal drug-binding mechanism, that rationalizes selectivity, affinity and long on-target residence time for kinase inhibitors. These new concepts, where protein dynamics in the drug-bound state plays the crucial role, can be applied to inhibitor design of targets outside the kinome.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 23 32%
Student > Ph. D. Student 14 20%
Student > Doctoral Student 6 8%
Student > Bachelor 6 8%
Student > Master 4 6%
Other 3 4%
Unknown 15 21%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 34%
Chemistry 13 18%
Agricultural and Biological Sciences 9 13%
Chemical Engineering 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 3 4%
Unknown 18 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 29 April 2021.
All research outputs
#7,058,070
of 23,090,520 outputs
Outputs from eLife
#10,534
of 14,014 outputs
Outputs of similar age
#121,711
of 328,563 outputs
Outputs of similar age from eLife
#276
of 349 outputs
Altmetric has tracked 23,090,520 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 14,014 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.9. This one is in the 24th percentile – i.e., 24% 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 328,563 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 62% of its contemporaries.
We're also able to compare this research output to 349 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.