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Structure-Based Druggability Assessment of the Mammalian Structural Proteome with Inclusion of Light Protein Flexibility

Overview of attention for article published in PLoS Computational Biology, July 2014
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3 X users

Citations

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29 Dimensions

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76 Mendeley
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Title
Structure-Based Druggability Assessment of the Mammalian Structural Proteome with Inclusion of Light Protein Flexibility
Published in
PLoS Computational Biology, July 2014
DOI 10.1371/journal.pcbi.1003741
Pubmed ID
Authors

Kathryn A. Loving, Andy Lin, Alan C. Cheng

Abstract

Advances reported over the last few years and the increasing availability of protein crystal structure data have greatly improved structure-based druggability approaches. However, in practice, nearly all druggability estimation methods are applied to protein crystal structures as rigid proteins, with protein flexibility often not directly addressed. The inclusion of protein flexibility is important in correctly identifying the druggability of pockets that would be missed by methods based solely on the rigid crystal structure. These include cryptic pockets and flexible pockets often found at protein-protein interaction interfaces. Here, we apply an approach that uses protein modeling in concert with druggability estimation to account for light protein backbone movement and protein side-chain flexibility in protein binding sites. We assess the advantages and limitations of this approach on widely-used protein druggability sets. Applying the approach to all mammalian protein crystal structures in the PDB results in identification of 69 proteins with potential druggable cryptic pockets.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Germany 2 3%
United Kingdom 2 3%
Japan 1 1%
Italy 1 1%
Unknown 67 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 30%
Student > Ph. D. Student 18 24%
Student > Master 9 12%
Professor 6 8%
Student > Bachelor 6 8%
Other 12 16%
Unknown 2 3%
Readers by discipline Count As %
Chemistry 24 32%
Agricultural and Biological Sciences 17 22%
Biochemistry, Genetics and Molecular Biology 13 17%
Computer Science 8 11%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Other 8 11%
Unknown 2 3%
Attention Score in Context

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 03 March 2015.
All research outputs
#15,309,599
of 25,593,129 outputs
Outputs from PLoS Computational Biology
#6,564
of 9,006 outputs
Outputs of similar age
#119,517
of 239,710 outputs
Outputs of similar age from PLoS Computational Biology
#101
of 163 outputs
Altmetric has tracked 25,593,129 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,006 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 25th percentile – i.e., 25% 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 239,710 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 163 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.