Computational Identification of Antibody Epitopes on the Dengue Virus NS1 Protein

Molecules. 2017 Apr 10;22(4):607. doi: 10.3390/molecules22040607.

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.

MeSH terms

  • Amino Acid Sequence
  • Antibodies, Monoclonal / chemistry*
  • Antibodies, Monoclonal / immunology*
  • Antibody Specificity / immunology
  • Binding Sites
  • Computer Simulation*
  • Dengue Virus* / classification
  • Dengue Virus* / immunology
  • Epitope Mapping* / methods
  • Epitopes / chemistry*
  • Epitopes / immunology*
  • Models, Molecular
  • Protein Binding
  • Protein Conformation
  • Structure-Activity Relationship
  • Viral Nonstructural Proteins / chemistry*
  • Viral Nonstructural Proteins / immunology*

Substances

  • Antibodies, Monoclonal
  • Epitopes
  • Viral Nonstructural Proteins