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A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis
Allostery is an essential regulatory mechanism of biological function. Allosteric sites are also pharmacologically relevant as they are often targeted with higher selectivity than orthosteric sites. However, a comprehensive map of allosteric sites poses experimental challenges because allostery is d...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4258684/ https://www.ncbi.nlm.nih.gov/pubmed/25482377 http://dx.doi.org/10.1038/srep07306 |
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author | Boulton, Stephen Akimoto, Madoka Selvaratnam, Rajeevan Bashiri, Amir Melacini, Giuseppe |
author_facet | Boulton, Stephen Akimoto, Madoka Selvaratnam, Rajeevan Bashiri, Amir Melacini, Giuseppe |
author_sort | Boulton, Stephen |
collection | PubMed |
description | Allostery is an essential regulatory mechanism of biological function. Allosteric sites are also pharmacologically relevant as they are often targeted with higher selectivity than orthosteric sites. However, a comprehensive map of allosteric sites poses experimental challenges because allostery is driven not only by structural changes, but also by modulations in dynamics that typically remain elusive to classical structure determination methods. An avenue to overcome these challenges is provided by the NMR chemical shift covariance analysis (CHESCA), as chemical shifts are exquisitely sensitive to redistributions in dynamic conformational ensembles. Here, we propose a set of complementary CHESCA algorithms designed to reliably detect allosteric networks with minimal occurrences of false positives or negatives. The proposed CHESCA toolset was tested for two allosteric proteins (PKA and EPAC) and is expected to complement traditional comparative structural analyses in the comprehensive identification of functionally relevant allosteric sites, including those in otherwise elusive partially unstructured regions. |
format | Online Article Text |
id | pubmed-4258684 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-42586842014-12-15 A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis Boulton, Stephen Akimoto, Madoka Selvaratnam, Rajeevan Bashiri, Amir Melacini, Giuseppe Sci Rep Article Allostery is an essential regulatory mechanism of biological function. Allosteric sites are also pharmacologically relevant as they are often targeted with higher selectivity than orthosteric sites. However, a comprehensive map of allosteric sites poses experimental challenges because allostery is driven not only by structural changes, but also by modulations in dynamics that typically remain elusive to classical structure determination methods. An avenue to overcome these challenges is provided by the NMR chemical shift covariance analysis (CHESCA), as chemical shifts are exquisitely sensitive to redistributions in dynamic conformational ensembles. Here, we propose a set of complementary CHESCA algorithms designed to reliably detect allosteric networks with minimal occurrences of false positives or negatives. The proposed CHESCA toolset was tested for two allosteric proteins (PKA and EPAC) and is expected to complement traditional comparative structural analyses in the comprehensive identification of functionally relevant allosteric sites, including those in otherwise elusive partially unstructured regions. Nature Publishing Group 2014-12-08 /pmc/articles/PMC4258684/ /pubmed/25482377 http://dx.doi.org/10.1038/srep07306 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Boulton, Stephen Akimoto, Madoka Selvaratnam, Rajeevan Bashiri, Amir Melacini, Giuseppe A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis |
title | A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis |
title_full | A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis |
title_fullStr | A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis |
title_full_unstemmed | A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis |
title_short | A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis |
title_sort | tool set to map allosteric networks through the nmr chemical shift covariance analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4258684/ https://www.ncbi.nlm.nih.gov/pubmed/25482377 http://dx.doi.org/10.1038/srep07306 |
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