Applying graph theory to protein structures: an atlas of coiled coils

Heal, J. W., Bartlett, G. J., Wood, C. W., Thomson, A. R. and Woolfson, D. N. (2018) Applying graph theory to protein structures: an atlas of coiled coils. Bioinformatics, 34(19), pp. 3316-3323. (doi:10.1093/bioinformatics/bty347) (PMID:29722888)

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Abstract

Motivation: To understand protein structure, folding and function fully and to design proteins de novo reliably, we must learn from natural protein structures that have been characterised experimentally. The number of protein structures available is large and growing exponentially, which makes this task challenging. Indeed, computational resources are becoming increasingly important for classifying and analysing this resource. Here, we use tools from graph theory to define an atlas classification scheme for automatically categorising certain protein substructures. Results: Focusing on the α-helical coiled coils, which are ubiquitous protein-structure and protein-protein interaction motifs, we present a suite of computational resources designed for analysing these assemblies. iSOCKET enables interactive analysis of side-chain packing within proteins to identify coiled coils automatically and with considerable user control. Applying a graph theory-based atlas classification scheme to structures identified by iSOCKET gives the Atlas of Coiled Coils, a fully automated, updated overview of extant coiled coils. The utility of this approach is illustrated with the first formal classification of an emerging subclass of coiled coils called α-helical barrels. Furthermore, in the Atlas, the known coiled-coil universe is presented alongside a partial enumeration of the ‘dark matter’ of coiled-coil structures; i.e., those coiled-coil architectures that are theoretically possible but have not been observed to date, and thus present defined targets for protein design. Availability: iSOCKET is available as part of the open-source GitHub repository associated with this work (https://github.com/woolfson-group/isocket). This repository also contains all the data generated when classifying the protein graphs. The Atlas of Coiled Coils is available at: http://coiledcoils.chm.bris.ac.uk/atlas/app.

Item Type:Articles
Additional Information:This work was supported by grants from the BBSRC (BB/J008990/1) and the ERC (340764) to DNW. CWW was supported by the BBSRC South West Doctoral Training Partnership. DNW holds a Royal Society Wolfson Research Merit Award (WM140008).
Keywords:Statistics and probability, computational theory and mathematics, biochemistry, molecular biology, computational mathematics, computer science applications
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Thomson, Dr Drew
Authors: Heal, J. W., Bartlett, G. J., Wood, C. W., Thomson, A. R., and Woolfson, D. N.
College/School:College of Science and Engineering > School of Chemistry
Journal Name:Bioinformatics
Publisher:Oxford University Press
ISSN:1367-4803
ISSN (Online):1460-2059
Published Online:02 May 2018
Copyright Holders:Copyright © 2018 The Authors
First Published:First published in Bioinformatics 34(19):3316-3323
Publisher Policy:Reproduced under a Creative Commons License

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