Abstract

Dengue fever is caused by the mosquito-borne virus termed (DENV). However, DENV-2 has been identified as the most prevalent amongst the Indonesian pediatric urban population, in contrast with the other four serotypes. Therefore, it is important to reduce severe infection risk by adopting preventive measures, including through vaccine development. The aim of this study, therefore is to use various in silico tools in the design of epitope-based peptide vaccines (T-cell and B-cell types), based on the DENV-2 envelope glycoprotein sequences available. Therefore, in silico methods were adopted in the analysis of the retrieved protein sequences. This technique was required to determine the most immunogenic protein, and is achieved through conservancy analysis, epitope identification, molecular simulation, and allergenicity assessment. Furthermore, B4XPM1, and KAWLVHRQW were identified from positions 204-212, while the 77 to 85 peptide region was considered the most potent T-cell and B-cell epitopes. The interaction between KAWLVHRQW and HLA-C*12:03 occurs with maximum population coverage, alongside high conservancy (96.98%) and binding affinity. These results indicated a potential for the designed epitopes to demonstrate high immunity against DENV-2.

Highlights

  • The mosquito-borne dengue virus (DENV) is a single positive-stranded RNA of Flavivirus, known to instigate dengue fever (DF)

  • Subsequent stages commonly feature dengue hemorrhagic fever (DHF), which is implicated in plasma leakage, where further outflow into the interstitial spaces have been associated with dengue shock syndrome (DSS)

  • The epitopes with potential against DENV-2 were predicted using several in silico tools, through methods adapted from Dash et al (2017) with modifications in terms of the tools and target used

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Summary

H AYAT I

Vol 27 No 3, July 2020 228-240 DOI:10.4308/hjb.27.3.228 ISSN: 1978-3019 EISSN: 2086-4094. Gadjah Mada University, Faculty of Biology, Department of Tropical Biology, Daerah Istimewa Yogyakarta, Indonesia. Article history: Received October 28, 2019 Received in revised form June 19, 2020 Accepted June 30, 2020

Introduction
Materials and Methods
T-Cell Epitope Identification and Conservancy Analysis
Prediction of Population Coverage and Allergenicity Assessment
Molecular Simulation Analysis of HLAAllele Interaction
Evolutionary Analysis and Antigenicity Prediction of the E Sequences
T-cell Epitope Identification and Conservancy Analysis
Discussion
Full Text
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