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Druggable Protein Interaction Sites Are More Predisposed to Surface Pocket Formation than the Rest of the Protein Surface

Overview of attention for article published in PLoS Computational Biology, March 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

blogs
1 blog
facebook
1 Facebook page
f1000
1 research highlight platform

Citations

dimensions_citation
82 Dimensions

Readers on

mendeley
144 Mendeley
citeulike
7 CiteULike
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Title
Druggable Protein Interaction Sites Are More Predisposed to Surface Pocket Formation than the Rest of the Protein Surface
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002951
Pubmed ID
Authors

David K. Johnson, John Karanicolas

Abstract

Despite intense interest and considerable effort via high-throughput screening, there are few examples of small molecules that directly inhibit protein-protein interactions. This suggests that many protein interaction surfaces may not be intrinsically "druggable" by small molecules, and elevates in importance the few successful examples as model systems for improving our fundamental understanding of druggability. Here we describe an approach for exploring protein fluctuations enriched in conformations containing surface pockets suitable for small molecule binding. Starting from a set of seven unbound protein structures, we find that the presence of low-energy pocket-containing conformations is indeed a signature of druggable protein interaction sites and that analogous surface pockets are not formed elsewhere on the protein. We further find that ensembles of conformations generated with this biased approach structurally resemble known inhibitor-bound structures more closely than equivalent ensembles of unbiased conformations. Collectively these results suggest that "druggability" is a property encoded on a protein surface through its propensity to form pockets, and inspire a model in which the crude features of the predisposed pocket(s) restrict the range of complementary ligands; additional smaller conformational changes then respond to details of a particular ligand. We anticipate that the insights described here will prove useful in selecting protein targets for therapeutic intervention.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 144 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
Germany 2 1%
United States 2 1%
Ireland 1 <1%
India 1 <1%
Canada 1 <1%
France 1 <1%
Spain 1 <1%
Russia 1 <1%
Other 0 0%
Unknown 131 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 28%
Researcher 39 27%
Student > Master 12 8%
Student > Bachelor 10 7%
Professor 9 6%
Other 19 13%
Unknown 14 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 36 25%
Agricultural and Biological Sciences 34 24%
Chemistry 29 20%
Computer Science 11 8%
Pharmacology, Toxicology and Pharmaceutical Science 6 4%
Other 14 10%
Unknown 14 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 March 2022.
All research outputs
#5,327,963
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#4,065
of 8,960 outputs
Outputs of similar age
#42,878
of 207,691 outputs
Outputs of similar age from PLoS Computational Biology
#42
of 150 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 79th 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 54% 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 207,691 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 79% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.