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An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein
Recently, progress has been made in the development of vaccines and monoclonal antibody cocktails that target the Ebola coat glycoprotein (GP). Based on the mutation rates for Ebola virus given its natural sequence evolution, these treatment strategies are likely to impose additional selection press...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5387726/ https://www.ncbi.nlm.nih.gov/pubmed/28397835 http://dx.doi.org/10.1038/srep45886 |
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author | Quinlan, Devin S. Raman, Rahul Tharakaraman, Kannan Subramanian, Vidya del Hierro, Gabriella Sasisekharan, Ram |
author_facet | Quinlan, Devin S. Raman, Rahul Tharakaraman, Kannan Subramanian, Vidya del Hierro, Gabriella Sasisekharan, Ram |
author_sort | Quinlan, Devin S. |
collection | PubMed |
description | Recently, progress has been made in the development of vaccines and monoclonal antibody cocktails that target the Ebola coat glycoprotein (GP). Based on the mutation rates for Ebola virus given its natural sequence evolution, these treatment strategies are likely to impose additional selection pressure to drive acquisition of mutations in GP that escape neutralization. Given the high degree of sequence conservation among GP of Ebola viruses, it would be challenging to determine the propensity of acquiring mutations in response to vaccine or treatment with one or a cocktail of monoclonal antibodies. In this study, we analyzed the mutability of each residue using an approach that captures the structural constraints on mutability based on the extent of its inter-residue interaction network within the three-dimensional structure of the trimeric GP. This analysis showed two distinct clusters of highly networked residues along the GP(1)-GP(2) interface, part of which overlapped with epitope surfaces of known neutralizing antibodies. This network approach also permitted us to identify additional residues in the network of the known hotspot residues of different anti-Ebola antibodies that would impact antibody-epitope interactions. |
format | Online Article Text |
id | pubmed-5387726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53877262017-04-14 An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein Quinlan, Devin S. Raman, Rahul Tharakaraman, Kannan Subramanian, Vidya del Hierro, Gabriella Sasisekharan, Ram Sci Rep Article Recently, progress has been made in the development of vaccines and monoclonal antibody cocktails that target the Ebola coat glycoprotein (GP). Based on the mutation rates for Ebola virus given its natural sequence evolution, these treatment strategies are likely to impose additional selection pressure to drive acquisition of mutations in GP that escape neutralization. Given the high degree of sequence conservation among GP of Ebola viruses, it would be challenging to determine the propensity of acquiring mutations in response to vaccine or treatment with one or a cocktail of monoclonal antibodies. In this study, we analyzed the mutability of each residue using an approach that captures the structural constraints on mutability based on the extent of its inter-residue interaction network within the three-dimensional structure of the trimeric GP. This analysis showed two distinct clusters of highly networked residues along the GP(1)-GP(2) interface, part of which overlapped with epitope surfaces of known neutralizing antibodies. This network approach also permitted us to identify additional residues in the network of the known hotspot residues of different anti-Ebola antibodies that would impact antibody-epitope interactions. Nature Publishing Group 2017-04-11 /pmc/articles/PMC5387726/ /pubmed/28397835 http://dx.doi.org/10.1038/srep45886 Text en Copyright © 2017, The Author(s) 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 to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Quinlan, Devin S. Raman, Rahul Tharakaraman, Kannan Subramanian, Vidya del Hierro, Gabriella Sasisekharan, Ram An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein |
title | An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein |
title_full | An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein |
title_fullStr | An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein |
title_full_unstemmed | An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein |
title_short | An inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoprotein |
title_sort | inter-residue network model to identify mutational-constrained regions on the ebola coat glycoprotein |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5387726/ https://www.ncbi.nlm.nih.gov/pubmed/28397835 http://dx.doi.org/10.1038/srep45886 |
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