Epitope-Based Vaccine Design with Bioinformatics Approach to Suppress Spike Glycoprotein of SARS-CoV-2
Abstract
Vaccination is one of the main prevention of the spread of Covid-19. Technological engineering based on virus attenuation has been applied in vaccine development. This study aims to obtain an epitope-based vaccine design with low risk of allergic reactions, safe, and inexpensive.
The design of the vaccine was conducted by the collection of SARS-CoV-2 sequence data, phylogenetic analysis, prediction of protein antigenicity, and identification of CD 8+ T cell epitopes. Furthermore, epitope conservation and immunogenicity prediction, as well as molecular docking analysis were carried out to see the interaction between epitopes and alleles. The next step was B cell epitope prediction, population coverage prediction, construction and visualization of vaccine design, structural analysis and validation, interaction analysis between vaccines with TLR 3 and TLR 4, and evaluation of vaccine design immunogenicity. All stages were carried out using the appropriate webserver.
The designed vaccine had an antigenicity of 0.5134, not toxic, and not allergenic. The physicochemical parameters met the requirements except for the molecular weight which was less than 40 KDa. The designed vaccine was predicted to have a population coverage of 95.14% for the Indonesian population. The results of the immunogenicity prediction of the vaccine design showed an increase of IgM and IgG until day 35.
References
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[2]. Pormohammad A, Zarei M, Ghorbani S, Mohammadi M, Razizadeh MH, Turner DL, et al. Efficacy and Safety of COVID-19 Vaccines: A Systematic Review and Meta-Analysis of Randomized Clinical Trials. Vaccines. 2021;9(467):1–21.
[3]. Bande F, Arshad SS, Hair Bejo M, Moeini H, Omar AR. Progress and challenges toward the development of vaccines against avian infectious bronchitis. J Immunol Res. 2015;2015.
[4]. Flingai S, Czerwonko M, Goodman J, Kudchodkar SB, Muthumani K, Weiner DB. Synthetic DNA vaccines: Improved vaccine potency by electroporation and co-delivered genetic adjuvants. Front Immunol. 2013;4(NOV):1–10.
[5]. Ingrid Lobo. Basic Local Alignment Search Tool (BLAST). Nat Educ. 2008;1(1):215.
[6]. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35(6):1547–9.
[7]. Vita R, Mahajan S, Overton JA, Dhanda SK, Martini S, Cantrell JR, et al. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Res. 2019;47(D1):D339–43.
[8]. Wang H, Zhang Y, Huang B, Deng W, Quan Y, Wang W. Development of an Inactivated Vaccine Candidate, BBIBP-CorV, with Potent Protection against SARSCoV- 2. Cell. 2020;182(August):713–721.
[9]. Yan Y, Tao H, He J, Huang SY. The HDOCK server for integrated protein–protein docking. Nat Protoc [Internet]. 2020;15(5):1829–52. Available from: http://dx.doi.org/10.1038/s41596-020-0312-x
[10]. Larsen JEP, Lund O, Nielsen M. Improved method for predicting linear B-cell epitopes. Immunome Res. 2006;2(1):2.
[11]. Jespersen MC, Peters B, Nielsen M, Marcatili P. BepiPred-2.0: Improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 2017;45(W1):W24–9.
[12]. Bui HH, Sidney J, Dinh K, Southwood S, Newman MJ, Sette A. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics. 2006;7:1–5.
[13]. Yang J, Anishchenko I, Park H, Peng Z, Ovchinnikov S, Baker D. Improved protein structure prediction using predicted interresidue orientations. Proc Natl Acad Sci U S A. 2020;117(3):1496–503.
[14]. Abraham Peele K, Srihansa T, Krupanidhi S, Ayyagari VS, Venkateswarulu TC. Design of multi-epitope vaccine candidate against SARS-CoV-2: a in-silico study. J Biomol Struct Dyn [Internet]. 2020;39(10):1–9. Available from: https://doi.org/10.1080/07391102.2020.1770127
[15]. Mahram A, Herbordt MC. Fast and accurate NCBI BLASTP. 2010;73.
[16]. Dimitrov I, Bangov I, Flower DR, Doytchinova I. AllerTOP v.2 - A server for in silico prediction of allergens. J Mol Model. 2014;20(6).
[17]. Bjellqvist B, Hughes GJ, Pasquali C, Paquet N, Ravier F, Sanchez J ‐C, et al. The focusing positions of polypeptides in immobilized pH gradients can be predicted from their amino acid sequences. Electrophoresis. 1993;14(1):1023–31.
[18]. Heo L, Park H, Seok C. GalaxyRefine: Protein structure refinement driven by side-chain repacking. Nucleic Acids Res. 2013;41(Web Server issue):384–8.
[19]. Farhani I, Nezafat N, Mahmoodi S. Designing a Novel Multi-epitope Peptide Vaccine Against Pathogenic Shigella spp. Based Immunoinformatics Approaches. Int J Pept Res Ther [Internet]. 2019;25(2):541–53. Available from: http://dx.doi.org/10.1007/s10989-018-9698-5
[20]. Jiménez-García B, Pons C, Fernández-Recio J. pyDockWEB: A web server for rigid-body protein-protein docking using electrostatics and desolvation scoring. Bioinformatics. 2013;29(13):1698–9.
[21]. Rapin N, Lund O, Bernaschi M, Castiglione F. Computational immunology meets bioinformatics: The use of prediction tools for molecular binding in the simulation of the immune system. PLoS One. 2010;5(4).
[22]. Kroger AT, Sumaya C V., Pickering LK, Atkinson WL. General Recommendations on Immunization Recommendations. Recomm Reports. 2011;60(2):61–85.
[23]. Kumar S, Tamura K, Jakobsen IB, Nei M. MEGA2: Molecular evolutionary genetics analysis software. Bioinformatics. 2002;17(12):1244–5.
[24]. Flower DR, Doytchinova I, Zaharieva N, Dimitrov I. Immunogenicity Prediction by VaxiJen: A Ten Year Overview. J Proteomics Bioinform. 2017;10(11):298–310.
[25]. Naz A, Shahid F, Butt TT, Awan FM, Ali A, Malik A. Designing Multi-Epitope Vaccines to Combat Emerging Coronavirus Disease 2019 (COVID-19) by Employing Immuno-Informatics Approach. Vol. 11, Frontiers in Immunology. 2020.
[26]. Rakib A, Sami SA, Mimi NJ, Chowdhury MM, Eva TA, Nainu F, et al. Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein. Comput Biol Med [Internet]. 2020;124(May):103967. Available from: https://doi.org/10.1016/j.compbiomed.2020.103967
[27]. Deléage G. ALIGNSEC: viewing protein secondary structure predictions within large multiple sequence alignments. Bioinformatics. 2017;33(24):3991–2.
[28]. Tahir ul Qamar M, Rehman A, Tusleem K, Ashfaq UA, Qasim M, Zhu X, et al. Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches. PLoS One [Internet]. 2020;15(12 December 2020):1–25. Available from: http://dx.doi.org/10.1371/journal.pone.0244176
[29]. Dar HA, Waheed Y, Najmi MH, Ismail S, Hetta HF, Ali A, et al. Multiepitope Subunit Vaccine Design against COVID-19 Based on the Spike Protein of SARS-CoV-2: An in Silico Analysis. J Immunol Res. 2020;2020.
Published
2021-11-20
Section
Articles
