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An assessment of catalytic residue 3D ensembles for the prediction of enzyme function

Overview of attention for article published in BMC Bioinformatics, November 2015
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Title
An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
Published in
BMC Bioinformatics, November 2015
DOI 10.1186/s12859-015-0807-6
Pubmed ID
Authors

Clemens Žváček, Gerald Friedrichs, Leonhard Heizinger, Rainer Merkl

Abstract

The central element of each enzyme is the catalytic site, which commonly catalyzes a single biochemical reaction with high specificity. It was unclear to us how often sites that catalyze the same or highly similar reactions evolved on different, i. e. non-homologous protein folds and how similar their 3D poses are. Both similarities are key criteria for assessing the usability of pose comparison for function prediction. We have analyzed the SCOP database on the superfamily level in order to estimate the number of non-homologous enzymes possessing the same function according to their EC number. 89 % of the 873 substrate-specific functions (four digit EC number) assigned to mono-functional, single-domain enzymes were only found in one superfamily. For a reaction-specific grouping (three digit EC number), this value dropped to 35 %, indicating that in approximately 65 % of all enzymes the same function evolved in two or more non-homologous proteins. For these isofunctional enzymes, structural similarity of the catalytic sites may help to predict function, because neither high sequence similarity nor identical folds are required for a comparison. To assess the specificity of catalytic 3D poses, we compiled the redundancy-free set ENZ_SITES, which comprises 695 sites, whose composition and function are well-defined. We compared their poses with the help of the program Superpose3D and determined classification performance. If the sites were from different superfamilies, the number of true and false positive predictions was similarly high, both for a coarse and a detailed grouping of enzyme function. Moreover, classification performance did not improve drastically, if we additionally used homologous sites to predict function. For a large number of enzymatic functions, dissimilar sites evolved that catalyze the same reaction and it is the individual substrate that determines the arrangement of the catalytic site and its local environment. These substrate-specific requirements turn the comparison of catalytic residues into a weak classifier for the prediction of enzyme function.

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Geographical breakdown

Country Count As %
United Kingdom 1 5%
France 1 5%
Unknown 17 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 21%
Student > Bachelor 2 11%
Student > Postgraduate 2 11%
Student > Ph. D. Student 2 11%
Student > Master 2 11%
Other 2 11%
Unknown 5 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 26%
Biochemistry, Genetics and Molecular Biology 2 11%
Computer Science 2 11%
Chemistry 2 11%
Medicine and Dentistry 2 11%
Other 1 5%
Unknown 5 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 04 November 2015.
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#18,430,119
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Outputs from BMC Bioinformatics
#6,320
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Outputs of similar age
#205,240
of 285,322 outputs
Outputs of similar age from BMC Bioinformatics
#135
of 153 outputs
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