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Functional Analysis of Enzyme Families Using Residue-Residue Coevolution Similarity Networks

Christian Atallah, David James Skelton, Simon J. Charnock, Anil Wipat
doi: https://doi.org/10.1101/646539
Christian Atallah
1School of Computing, Newcastle University, Newcastle upon Tyne, NE4 5TG, United Kingdom
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David James Skelton
1School of Computing, Newcastle University, Newcastle upon Tyne, NE4 5TG, United Kingdom
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Simon J. Charnock
2Prozomix Limited, Haltwhistle, NE49 9HN, United Kingdom
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Anil Wipat
1School of Computing, Newcastle University, Newcastle upon Tyne, NE4 5TG, United Kingdom
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  • For correspondence: anil.wipat@ncl.ac.uk
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Abstract

Motivation Residue-residue coevolution has been used to elucidate structural information of enzymes. Networks of coevolution patterns have also been analyzed to discover residues important for the function of individual enzymes. In this work, we take advantage of the functional importance of coevolving residues to perform network-based clustering of subsets of enzyme families based on similarities of their coevolution patterns, or “Coevolution Similarity Networks”. The power of these networks in the functional analysis of sets of enzymes is explored in detail, using Sequence Similarity Networks as a benchmark.

Results A novel method to produce protein-protein networks showing the similarity between proteins based on the matches in the patterns of their intra-residue residue coevolution is described. The properties of these co-evolution similarity networks (CSNs) was then explored, especially in comparison to widely used sequence similarity networks (SSNs). We focused on the predictive power of CSNs and SSNs for the annotation of enzyme substrate specificity in the form of Enzyme Commission (EC) numbers using a label propagation approach. A method for systematically defining the threshold necessary to produce the optimally predictive CSNs and SSNs is described. Our data shows that, for the two protein families we analyse, CSNs show higher predictive power for the reannotation of substrate specificity for previously annotated enzymes retrieved from Swissprot. A topological analysis of both CSNs and SSNs revealed core similarities in the structure, topology and annotation distribution but also reveals a subset of nodes and edges that are unique to each network type, highlighting their complementarity. Overall, we propose CSNs as a new method for analysing the function enzyme families that complements, and offers advantages to, other network based methods for protein family analysis.

Availability Source code available on request.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 24, 2019.
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Functional Analysis of Enzyme Families Using Residue-Residue Coevolution Similarity Networks
Christian Atallah, David James Skelton, Simon J. Charnock, Anil Wipat
bioRxiv 646539; doi: https://doi.org/10.1101/646539
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Functional Analysis of Enzyme Families Using Residue-Residue Coevolution Similarity Networks
Christian Atallah, David James Skelton, Simon J. Charnock, Anil Wipat
bioRxiv 646539; doi: https://doi.org/10.1101/646539

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