tetano
Editor, Senior Moderator
Int J Pept Res Ther
. 2022;28(3):77.
doi: 10.1007/s10989-022-10382-5. Epub 2022 Mar 16.
Immunogenic Epitope-Based Vaccine Prediction from Surface Glycoprotein of MERS-CoV by Deploying Immunoinformatics Approach
Truc Ly Nguyen[SUP] 1 [/SUP], Youngho Lee[SUP] 2 [/SUP], Heebal Kim[SUP] 1 2 3 [/SUP]
Affiliations
Abstract
Middle East respiratory syndrome coronavirus (MERS-CoV) has caused a high mortality rate since its emergence in 2012 in the Middle East. Currently, no effective drug or vaccine is available for MERS-CoV. Supportive care and prevention are the only ways to manage infection. In this study, we identified an epitope-based vaccine that could be an optimal solution for the prevention of MERS-CoV infection. By deploying an immunoinformatics approach, we predicted a subunit vaccine based on the surface glycoprotein (S protein) of MERS-CoV. For this purpose, the proteome of the MERS-CoV spike protein was obtained from the NCBI GenBank database. Then, it was subjected to a check for allergenicity using the Allergen FP v.1.0 tool. The Vaxijen v.2.0 tool was used to conduct antigenicity tests for binding with major histocompatibility complex class I and II molecules. The solidity of the predicted epitope-allele docked complex was evaluated by a molecular dynamics simulation. After docking a total of eight epitopes from the MERS-CoV S protein, further analyses predicted their non-toxicity and therapeutic immunogenic properties. These epitopes have potential utility as vaccine candidates against MERS-CoV, to be validated by wet-lab testing.
Supplementary information: The online version contains supplementary material available at 10.1007/s10989-022-10382-5.
Keywords: Allergenicity; Antigenicity; Epitope vaccine; Immunoinformatics; Middle East respiratory syndrome (MERS).
. 2022;28(3):77.
doi: 10.1007/s10989-022-10382-5. Epub 2022 Mar 16.
Immunogenic Epitope-Based Vaccine Prediction from Surface Glycoprotein of MERS-CoV by Deploying Immunoinformatics Approach
Truc Ly Nguyen[SUP] 1 [/SUP], Youngho Lee[SUP] 2 [/SUP], Heebal Kim[SUP] 1 2 3 [/SUP]
Affiliations
- PMID: 35313444
- PMCID: PMC8924944
- DOI: 10.1007/s10989-022-10382-5
Abstract
Middle East respiratory syndrome coronavirus (MERS-CoV) has caused a high mortality rate since its emergence in 2012 in the Middle East. Currently, no effective drug or vaccine is available for MERS-CoV. Supportive care and prevention are the only ways to manage infection. In this study, we identified an epitope-based vaccine that could be an optimal solution for the prevention of MERS-CoV infection. By deploying an immunoinformatics approach, we predicted a subunit vaccine based on the surface glycoprotein (S protein) of MERS-CoV. For this purpose, the proteome of the MERS-CoV spike protein was obtained from the NCBI GenBank database. Then, it was subjected to a check for allergenicity using the Allergen FP v.1.0 tool. The Vaxijen v.2.0 tool was used to conduct antigenicity tests for binding with major histocompatibility complex class I and II molecules. The solidity of the predicted epitope-allele docked complex was evaluated by a molecular dynamics simulation. After docking a total of eight epitopes from the MERS-CoV S protein, further analyses predicted their non-toxicity and therapeutic immunogenic properties. These epitopes have potential utility as vaccine candidates against MERS-CoV, to be validated by wet-lab testing.
Supplementary information: The online version contains supplementary material available at 10.1007/s10989-022-10382-5.
Keywords: Allergenicity; Antigenicity; Epitope vaccine; Immunoinformatics; Middle East respiratory syndrome (MERS).