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dc.contributor.authorQuinlan, Devin Scott
dc.contributor.authorRaman, Rahul
dc.contributor.authorTharakaraman, Kannan
dc.contributor.authorSubramanian, Vidya
dc.contributor.authordel Hierro, Gabriella A.
dc.contributor.authorSasisekharan, Ram
dc.date.accessioned2017-06-21T13:14:50Z
dc.date.available2017-06-21T13:14:50Z
dc.date.issued2017-04
dc.date.submitted2016-09
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/1721.1/110096
dc.description.abstractRecently, 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 GP1-GP2 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.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (MERIT award R37 GM057073-13)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Research Project Grant 1R01AI111395-01)en_US
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/srep45886en_US
dc.rightsCreative Commons Attribution 4.0 International Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleAn inter-residue network model to identify mutational-constrained regions on the Ebola coat glycoproteinen_US
dc.typeArticleen_US
dc.identifier.citationQuinlan, Devin S., Rahul Raman, Kannan Tharakaraman, Vidya Subramanian, Gabriella del Hierro, and Ram Sasisekharan. “An Inter-Residue Network Model to Identify Mutational-Constrained Regions on the Ebola Coat Glycoprotein.” Scientific Reports 7 (April 11, 2017): 45886.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.contributor.mitauthorQuinlan, Devin Scott
dc.contributor.mitauthorRaman, Rahul
dc.contributor.mitauthorTharakaraman, Kannan
dc.contributor.mitauthorSubramanian, Vidya
dc.contributor.mitauthordel Hierro, Gabriella A.
dc.contributor.mitauthorSasisekharan, Ram
dc.relation.journalScientific Reportsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsQuinlan, Devin S.; Raman, Rahul; Tharakaraman, Kannan; Subramanian, Vidya; del Hierro, Gabriella; Sasisekharan, Ramen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-6977-7403
dc.identifier.orcidhttps://orcid.org/0000-0002-2085-7840
mit.licensePUBLISHER_CCen_US


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