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Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach.
Int J Biol Macromol. 2020 Dec 01; 164:871-883.IJ

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused COVID-19 disease in China. So far, no vaccine has licensed to protect against infection with COVID-19, therefore an effective COVID-19 vaccine needed. The aim of this study was to predict antigenic peptides of SARS-CoV-2 for designing the COVID-19 vaccine using immunoinformatic analysis. In this study, T and B-cell epitopes of S protein were predicted and screened based on the antigenicity, toxicity, allergenicity, and cross-reactivity with human proteomes. The epitopes were joined by the appropriate linker. LT-IIc as an adjuvant was attached to the end of the structure. The secondary and 3D structure of the vaccine was predicted. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The proposed vaccine's binding affinity to the HLA-A11:01 and HLA-DRB1_01:01 molecule was evaluated by molecular docking. Using molecular dynamics, the stability of vaccine-HLA complexes was also evaluated. Finally, in silico gene cloning was performed in the pET30a (+) vector. The findings suggest that the current vaccine may be a promising vaccine to prevent SARS-CoV-2 infection.

Authors+Show Affiliations

Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.Cellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran.Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.Cellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran.Cellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran.Department of Tissue Engineering, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran. Electronic address: mor1361@gmail.com.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32682041

Citation

Sanami, Samira, et al. "Design of a Multi-epitope Vaccine Against SARS-CoV-2 Using Immunoinformatics Approach." International Journal of Biological Macromolecules, vol. 164, 2020, pp. 871-883.
Sanami S, Zandi M, Pourhossein B, et al. Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach. Int J Biol Macromol. 2020;164:871-883.
Sanami, S., Zandi, M., Pourhossein, B., Mobini, G. R., Safaei, M., Abed, A., Arvejeh, P. M., Chermahini, F. A., & Alizadeh, M. (2020). Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach. International Journal of Biological Macromolecules, 164, 871-883. https://doi.org/10.1016/j.ijbiomac.2020.07.117
Sanami S, et al. Design of a Multi-epitope Vaccine Against SARS-CoV-2 Using Immunoinformatics Approach. Int J Biol Macromol. 2020 Dec 1;164:871-883. PubMed PMID: 32682041.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach. AU - Sanami,Samira, AU - Zandi,Milad, AU - Pourhossein,Behzad, AU - Mobini,Gholam-Reza, AU - Safaei,Mohsen, AU - Abed,Atena, AU - Arvejeh,Pooria Mohammadi, AU - Chermahini,Fatemeh Amini, AU - Alizadeh,Morteza, Y1 - 2020/07/15/ PY - 2020/05/02/received PY - 2020/06/30/revised PY - 2020/07/07/accepted PY - 2020/7/19/pubmed PY - 2020/11/24/medline PY - 2020/7/19/entrez KW - COVID-19 KW - Epitopes KW - Vaccine SP - 871 EP - 883 JF - International journal of biological macromolecules JO - Int J Biol Macromol VL - 164 N2 - Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused COVID-19 disease in China. So far, no vaccine has licensed to protect against infection with COVID-19, therefore an effective COVID-19 vaccine needed. The aim of this study was to predict antigenic peptides of SARS-CoV-2 for designing the COVID-19 vaccine using immunoinformatic analysis. In this study, T and B-cell epitopes of S protein were predicted and screened based on the antigenicity, toxicity, allergenicity, and cross-reactivity with human proteomes. The epitopes were joined by the appropriate linker. LT-IIc as an adjuvant was attached to the end of the structure. The secondary and 3D structure of the vaccine was predicted. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The proposed vaccine's binding affinity to the HLA-A11:01 and HLA-DRB1_01:01 molecule was evaluated by molecular docking. Using molecular dynamics, the stability of vaccine-HLA complexes was also evaluated. Finally, in silico gene cloning was performed in the pET30a (+) vector. The findings suggest that the current vaccine may be a promising vaccine to prevent SARS-CoV-2 infection. SN - 1879-0003 UR - https://www.unboundmedicine.com/medline/citation/32682041/Design_of_a_multi_epitope_vaccine_against_SARS_CoV_2_using_immunoinformatics_approach_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0141-8130(20)33870-8 DB - PRIME DP - Unbound Medicine ER -