Zika is one of the most dreaded viruses which has left mankind crippled for over years. Current no vaccines for Zika are available in the market and only a few are in the clinical trials. The conventional vaccine approach uses live-attenuated or inactivated vaccines for administration which are unsafe and produces relapse of the disease. Considering the need for a safer vaccine, an immunoinformatics approach to design and develop a multi-epitope vaccine against Zika was conducted. Capsid, membrane and envelope proteins were retrieved from the database and were utilized to predict MHC class-I and class-II epitopes. The vaccine was constructed with a β-defensin at the N-terminal followed by CTL and the HTL joined together by respective linkers. Linear B-cell epitopes were predicted for the constructed vaccine followed by an assessment of physiological parameters. The vaccine was found to elicit an antigen response and was allergen safe. The vaccine construct was then modeled and the docked against the TLR4 receptor for understanding the capability of the vaccine to elicit an immune response. The docked complex was further simulated for 20 ns and an average of 13 hydrogen bonds was calculated from the trajectory. Finally, the vaccine construct was in-silico cloned into the pET28a(+) vector for affinity purification using His-tag. In a nutshell, the vaccine construct has a high potential to be developed as a vaccine against Zika. Further studies including experimental investigations and immunological studies will be required to validate the construct in a real-time scenario.
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The authors thank Centre for Automation and Instrumentation (CAI), NIT Warangal for providing the necessary computational facility to carry out the work. The author SS and SR acknowledge research fellowship from NIT Warangal.
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Mittal, A., Sasidharan, S., Raj, S. et al. Exploring the Zika Genome to Design a Potential Multiepitope Vaccine Using an Immunoinformatics Approach. Int J Pept Res Ther (2020) doi:10.1007/s10989-020-10020-y
- Multi-epitope vaccine
- MD simulation
- In-silico cloning