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Global Analysis of Small Molecule Binding to Related Protein Targets

Overview of attention for article published in PLoS Computational Biology, January 2012
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Title
Global Analysis of Small Molecule Binding to Related Protein Targets
Published in
PLoS Computational Biology, January 2012
DOI 10.1371/journal.pcbi.1002333
Pubmed ID
Authors

Felix A. Kruger, John P. Overington

Abstract

We report on the integration of pharmacological data and homology information for a large scale analysis of small molecule binding to related targets. Differences in small molecule binding have been assessed for curated pairs of human to rat orthologs and also for recently diverged human paralogs. Our analysis shows that in general, small molecule binding is conserved for pairs of human to rat orthologs. Using statistical tests, we identified a small number of cases where small molecule binding is different between human and rat, some of which had previously been reported in the literature. Knowledge of species specific pharmacology can be advantageous for drug discovery, where rats are frequently used as a model system. For human paralogs, we demonstrate a global correlation between sequence identity and the binding of small molecules with equivalent affinity. Our findings provide an initial general model relating small molecule binding and sequence divergence, containing the foundations for a general model to anticipate and predict within-target-family selectivity.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 5%
United States 5 5%
Germany 2 2%
Israel 1 <1%
Denmark 1 <1%
Portugal 1 <1%
Spain 1 <1%
Poland 1 <1%
Unknown 89 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 39%
Student > Ph. D. Student 21 20%
Student > Bachelor 9 8%
Student > Master 8 8%
Other 8 8%
Other 17 16%
Unknown 2 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 35%
Biochemistry, Genetics and Molecular Biology 19 18%
Chemistry 17 16%
Computer Science 9 8%
Pharmacology, Toxicology and Pharmaceutical Science 6 6%
Other 10 9%
Unknown 8 8%