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Structural Characteristics of Novel Protein Folds

Overview of attention for article published in PLoS Computational Biology, April 2010
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Title
Structural Characteristics of Novel Protein Folds
Published in
PLoS Computational Biology, April 2010
DOI 10.1371/journal.pcbi.1000750
Pubmed ID
Authors

Narcis Fernandez-Fuentes, Joseph M. Dybas, Andras Fiser

Abstract

Folds are the basic building blocks of protein structures. Understanding the emergence of novel protein folds is an important step towards understanding the rules governing the evolution of protein structure and function and for developing tools for protein structure modeling and design. We explored the frequency of occurrences of an exhaustively classified library of supersecondary structural elements (Smotifs), in protein structures, in order to identify features that would define a fold as novel compared to previously known structures. We found that a surprisingly small set of Smotifs is sufficient to describe all known folds. Furthermore, novel folds do not require novel Smotifs, but rather are a new combination of existing ones. Novel folds can be typified by the inclusion of a relatively higher number of rarely occurring Smotifs in their structures and, to a lesser extent, by a novel topological combination of commonly occurring Smotifs. When investigating the structural features of Smotifs, we found that the top 10% of most frequent ones have a higher fraction of internal contacts, while some of the most rare motifs are larger, and contain a longer loop region.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 7%
Canada 2 2%
Portugal 1 <1%
Italy 1 <1%
India 1 <1%
United Kingdom 1 <1%
Germany 1 <1%
Denmark 1 <1%
Korea, Republic of 1 <1%
Other 2 2%
Unknown 105 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 32%
Researcher 39 31%
Professor 8 6%
Student > Bachelor 7 6%
Student > Postgraduate 6 5%
Other 18 14%
Unknown 7 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 64 51%
Biochemistry, Genetics and Molecular Biology 28 22%
Computer Science 13 10%
Engineering 3 2%
Chemistry 3 2%
Other 6 5%
Unknown 8 6%