Computational Identification of Antibody Epitopes on the Dengue Virus NS1 Protein

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Publication Details

Author list: Jones ML, Legge FS, Lebani K, Mahler SM, Young PR, Watterson D, Treutlein HR, Zeng J

Publisher: MDPI

Place: BASEL

Publication year: 2017

Journal: Molecules (1420-3049)

Journal acronym: MOLECULES

Volume number: 22

Issue number: 4

Number of pages: 21

ISSN: 1420-3049

eISSN: 1420-3049

Languages: English-Great Britain (EN-GB)

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Abstract

We have previously described a method to predict antigenic epitopes on proteins recognized by specific antibodies. Here we have applied this method to identify epitopes on the NS1 proteins of the four Dengue virus serotypes (DENV1-4) that are bound by a small panel of monoclonal antibodies 1H7.4, 1G5.3 and Gus2. Several epitope regions were predicted for these antibodies and these were found to reflect the experimentally observed reactivities. The known binding epitopes on DENV2 for the antibodies 1H7.4 and 1G5.3 were identified, revealing the reasons for the serotype specificity of 1H7.4 and 1G5.3, and the non-selectivity of Gus2. As DENV NS1 is critical for virus replication and a key vaccine candidate, epitope prediction will be valuable in designing appropriate vaccine control strategies. The ability to predict potential epitopes by computational methods significantly reduces the amount of experimental work required to screen peptide libraries for epitope mapping.

Keywords

antibody Epitopes, computational modeling, dengue virus

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