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A Comprehensive Survey of Small-Molecule Binding Pockets in Proteins

Overview of attention for article published in PLoS Computational Biology, October 2013
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Title
A Comprehensive Survey of Small-Molecule Binding Pockets in Proteins
Published in
PLoS Computational Biology, October 2013
DOI 10.1371/journal.pcbi.1003302
Pubmed ID
Authors

Mu Gao, Jeffrey Skolnick

Abstract

Many biological activities originate from interactions between small-molecule ligands and their protein targets. A detailed structural and physico-chemical characterization of these interactions could significantly deepen our understanding of protein function and facilitate drug design. Here, we present a large-scale study on a non-redundant set of about 20,000 known ligand-binding sites, or pockets, of proteins. We find that the structural space of protein pockets is crowded, likely complete, and may be represented by about 1,000 pocket shapes. Correspondingly, the growth rate of novel pockets deposited in the Protein Data Bank has been decreasing steadily over the recent years. Moreover, many protein pockets are promiscuous and interact with ligands of diverse scaffolds. Conversely, many ligands are promiscuous and interact with structurally different pockets. Through a physico-chemical and structural analysis, we provide insights into understanding both pocket promiscuity and ligand promiscuity. Finally, we discuss the implications of our study for the prediction of protein-ligand interactions based on pocket comparison.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 202 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 3 1%
Spain 2 <1%
Norway 2 <1%
Brazil 1 <1%
Finland 1 <1%
Czechia 1 <1%
Canada 1 <1%
Germany 1 <1%
Other 4 2%
Unknown 181 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 63 31%
Researcher 48 24%
Student > Master 19 9%
Student > Bachelor 19 9%
Student > Doctoral Student 9 4%
Other 27 13%
Unknown 17 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 59 29%
Chemistry 40 20%
Biochemistry, Genetics and Molecular Biology 39 19%
Computer Science 16 8%
Pharmacology, Toxicology and Pharmaceutical Science 8 4%
Other 16 8%
Unknown 24 12%