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Immunoinformatic Analysis of T- and B-Cell Epitopes for SARS-CoV-2 Vaccine Design
 
 
Article

Vaccine Design from the Ensemble of Surface Glycoprotein Epitopes of SARS-CoV-2: An Immunoinformatics Approach

1
H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
2
Department of Biochemistry, Hazara University, Mansehra 21120, Pakistan
3
Jamil-ur-Rahman Center for Genome Research, PCMD, ICCBS, University of Karachi, Karachi 75270, Pakistan
4
Department of Biotechnology, Virtual University of Pakistan, Lahore 54000, Pakistan
5
Centre for Applied Molecular Biology, University of the Punjab, Lahore 53700, Pakistan
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Faculty of Sciences, University of Reims Champagne-Ardenne, CEDEX 2, 51687 Reims, France
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Department of Chemistry, Faculty of Science, University of Hradec Kralove, 50005 Hradec Kralove, Czech Republic
8
Department of Pharmacy, Abdul Wali Khan University Mardan, Mardan 23200, Pakistan
*
Authors to whom correspondence should be addressed.
Vaccines 2020, 8(3), 423; https://doi.org/10.3390/vaccines8030423
Received: 7 June 2020 / Revised: 9 July 2020 / Accepted: 20 July 2020 / Published: 28 July 2020
The present study aimed to work out a peptide-based multi-epitope vaccine against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We predicted different B-cell and T-cell epitopes by using the Immune Epitopes Database (IEDB). Homology modeling of the construct was done using SWISS-MODEL and then docked with different toll-like-receptors (TLR4, TLR7, and TLR8) using PatchDock, HADDOCK, and FireDock, respectively. From the overlapped epitopes, we designed five vaccine constructs C1–C5. Based on antigenicity, allergenicity, solubility, different physiochemical properties, and molecular docking scores, we selected the vaccine construct 1 (C1) for further processing. Docking of C1 with TLR4, TLR7, and TLR8 showed striking interactions with global binding energy of −43.48, −65.88, and −60.24 Kcal/mol, respectively. The docked complex was further simulated, which revealed that both molecules remain stable with minimum RMSF. Activation of TLRs induces downstream pathways to produce pro-inflammatory cytokines against viruses and immune system simulation shows enhanced antibody production after the booster dose. In conclusion, C1 was the best vaccine candidate among all designed constructs to elicit an immune response SARS-CoV-2 and combat the coronavirus disease (COVID-19). View Full-Text
Keywords: vaccine; multi-epitopes; antigenicity; allergenicity; coronavirus; pneumonia vaccine; multi-epitopes; antigenicity; allergenicity; coronavirus; pneumonia
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MDPI and ACS Style

Rahman, N.; Ali, F.; Basharat, Z.; Shehroz, M.; Khan, M.K.; Jeandet, P.; Nepovimova, E.; Kuca, K.; Khan, H. Vaccine Design from the Ensemble of Surface Glycoprotein Epitopes of SARS-CoV-2: An Immunoinformatics Approach. Vaccines 2020, 8, 423. https://doi.org/10.3390/vaccines8030423

AMA Style

Rahman N, Ali F, Basharat Z, Shehroz M, Khan MK, Jeandet P, Nepovimova E, Kuca K, Khan H. Vaccine Design from the Ensemble of Surface Glycoprotein Epitopes of SARS-CoV-2: An Immunoinformatics Approach. Vaccines. 2020; 8(3):423. https://doi.org/10.3390/vaccines8030423

Chicago/Turabian Style

Rahman, Noor, Fawad Ali, Zarrin Basharat, Muhammad Shehroz, Muhammad Kazim Khan, Philippe Jeandet, Eugenie Nepovimova, Kamil Kuca, and Haroon Khan. 2020. "Vaccine Design from the Ensemble of Surface Glycoprotein Epitopes of SARS-CoV-2: An Immunoinformatics Approach" Vaccines 8, no. 3: 423. https://doi.org/10.3390/vaccines8030423

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