BASILIScan: a tool for high-throughput analysis of intrinsic disorder patterns in homologous proteins
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Published version
Author(s)
Barski, Michal
Type
Journal Article
Abstract
Background
Intrinsic structural disorder is a common property of many proteins, especially in eukaryotic and virus proteomes. The tendency of some proteins or protein regions to exist in a disordered state usually precludes their structural characterisation and renders them especially difficult for experimental handling after recombinant expression.
Results
A new intuitive, publicly-available computational resource, called BASILIScan, is presented here. It provides a BLAST-based search for close homologues of the protein of interest, integrated with a simultaneous prediction of intrinsic disorder together with a robust data viewer and interpreter. This allows for a quick, high-throughput screening, scoring and selection of closely-related yet highly structured homologues of the protein of interest. Comparative parallel analysis of the conservation of extended regions of disorder in multiple sequences is also offered. The use of BASILIScan and its capacity for yielding biologically applicable predictions is demonstrated. Using a high-throughput BASILIScan screen it is also shown that a large proportion of the human proteome displays homologous sequences of superior intrinsic structural order in many related species.
Conclusion
Through the swift identification of intrinsically stable homologues and poorly conserved disordered regions by the BASILIScan software, the chances of successful recombinant protein expression and compatibility with downstream applications such as crystallisation can be greatly increased.
Intrinsic structural disorder is a common property of many proteins, especially in eukaryotic and virus proteomes. The tendency of some proteins or protein regions to exist in a disordered state usually precludes their structural characterisation and renders them especially difficult for experimental handling after recombinant expression.
Results
A new intuitive, publicly-available computational resource, called BASILIScan, is presented here. It provides a BLAST-based search for close homologues of the protein of interest, integrated with a simultaneous prediction of intrinsic disorder together with a robust data viewer and interpreter. This allows for a quick, high-throughput screening, scoring and selection of closely-related yet highly structured homologues of the protein of interest. Comparative parallel analysis of the conservation of extended regions of disorder in multiple sequences is also offered. The use of BASILIScan and its capacity for yielding biologically applicable predictions is demonstrated. Using a high-throughput BASILIScan screen it is also shown that a large proportion of the human proteome displays homologous sequences of superior intrinsic structural order in many related species.
Conclusion
Through the swift identification of intrinsically stable homologues and poorly conserved disordered regions by the BASILIScan software, the chances of successful recombinant protein expression and compatibility with downstream applications such as crystallisation can be greatly increased.
Date Issued
2018-12-11
Date Acceptance
2018-11-28
Citation
BMC Genomics, 2018, 19
ISSN
1471-2164
Publisher
BioMed Central
Journal / Book Title
BMC Genomics
Volume
19
Copyright Statement
© The Author(s). 2018Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Subjects
06 Biological Sciences
11 Medical And Health Sciences
08 Information And Computing Sciences
Bioinformatics
Publication Status
Published