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Exploring the Evolution of Novel Enzyme Functions within Structurally Defined Protein Superfamilies

Overview of attention for article published in PLoS Computational Biology, March 2012
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Title
Exploring the Evolution of Novel Enzyme Functions within Structurally Defined Protein Superfamilies
Published in
PLoS Computational Biology, March 2012
DOI 10.1371/journal.pcbi.1002403
Pubmed ID
Authors

Nicholas Furnham, Ian Sillitoe, Gemma L. Holliday, Alison L. Cuff, Roman A. Laskowski, Christine A. Orengo, Janet M. Thornton

Abstract

In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life.

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Geographical breakdown

Country Count As %
United States 9 5%
United Kingdom 7 4%
France 3 2%
Portugal 2 1%
Switzerland 1 <1%
Austria 1 <1%
Australia 1 <1%
Italy 1 <1%
Germany 1 <1%
Other 7 4%
Unknown 162 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 31%
Student > Ph. D. Student 47 24%
Student > Bachelor 15 8%
Student > Master 12 6%
Professor 11 6%
Other 39 20%
Unknown 11 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 91 47%
Biochemistry, Genetics and Molecular Biology 58 30%
Computer Science 9 5%
Chemistry 9 5%
Environmental Science 2 1%
Other 9 5%
Unknown 17 9%