Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools
Background and Aim: SARS-CoV-2 is the causative agent of Coronavirus 2019 or COVID-19 in the world. Novel coronavirus disease is a respiratory disease. To date, there have been challenges in the treatment for COVID-19 and emerged new variants like UK B1.1.7. Accordingly, an effective prevention regi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Farname
2021-09-01
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| Series: | Iranian Journal of Medical Microbiology |
| Subjects: | |
| Online Access: | http://ijmm.ir/article-1-1390-en.html |
| _version_ | 1819003228945121280 |
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| author | Hassan Dariushnejad Vajihe Ghorbanzadeh Soheila Akbari Pejman Hashemzadeh |
| author_facet | Hassan Dariushnejad Vajihe Ghorbanzadeh Soheila Akbari Pejman Hashemzadeh |
| author_sort | Hassan Dariushnejad |
| collection | DOAJ |
| description | Background and Aim: SARS-CoV-2 is the causative agent of Coronavirus 2019 or COVID-19 in the world. Novel coronavirus disease is a respiratory disease. To date, there have been challenges in the treatment for COVID-19 and emerged new variants like UK B1.1.7. Accordingly, an effective prevention regime is needed for this infection, which covers most variants. The purpose of this research was to predict the conserved epitopes of Spike and Nucleocapsid proteins from SARS-CoV-2 for the design of a novel coronavirus 2019 multi-epitope vaccine using in silico tools.
Materials and Methods: Computational analysis and immunoinformatics approaches include identification of potential conserve epitopes and selection of epitopes based on allergenicity, toxicity, antigenicity, and molecular docking were used for epitope prediction and screening. In the next step, selected segments of the epitopes were attached by the suitable linkers. Finally, Maltese-bound protein (MBP) as an adjuvant was added to the novel vaccine structure. The secondary and third structures of the designed multi-epitope vaccine were predicted via immunoinformatics algorithms. Predicted structure refined and validated for attaining best stability. In the end, immunoinformatics evaluation, molecular docking, and molecular dynamics were performed to confirm vaccine efficiency. Codon optimization and in silico cloning were done to ensure the expression yield of the novel multi-epitope vaccine in the target host.
Results: This study showed that our data support the suggestion that the designed vaccine could induce immune responses against SARS-CoV-2 variants.
Conclusion: The structure designed had acceptable quality with software reviews. Further in vitro and in vivo experiments are needed to confirm the safety and immunogenicity of the candidate vaccine. |
| first_indexed | 2024-12-20T23:17:40Z |
| format | Article |
| id | doaj.art-689ed9610b7b4aa2b3eeb6801d6dbc22 |
| institution | Directory Open Access Journal |
| issn | 1735-8612 2345-4342 |
| language | English |
| last_indexed | 2024-12-20T23:17:40Z |
| publishDate | 2021-09-01 |
| publisher | Farname |
| record_format | Article |
| series | Iranian Journal of Medical Microbiology |
| spelling | doaj.art-689ed9610b7b4aa2b3eeb6801d6dbc222022-12-21T19:23:36ZengFarnameIranian Journal of Medical Microbiology1735-86122345-43422021-09-01155592605Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico ToolsHassan Dariushnejad0Vajihe Ghorbanzadeh1Soheila Akbari2Pejman Hashemzadeh3 Department of Medical Biotechnology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran Razi Herbal Medicines Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran Department of Obstetrics and Gynecology, Lorestan University of Medical Sciences, Khorramabad, Iran Department of Medical Biotechnology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran Background and Aim: SARS-CoV-2 is the causative agent of Coronavirus 2019 or COVID-19 in the world. Novel coronavirus disease is a respiratory disease. To date, there have been challenges in the treatment for COVID-19 and emerged new variants like UK B1.1.7. Accordingly, an effective prevention regime is needed for this infection, which covers most variants. The purpose of this research was to predict the conserved epitopes of Spike and Nucleocapsid proteins from SARS-CoV-2 for the design of a novel coronavirus 2019 multi-epitope vaccine using in silico tools. Materials and Methods: Computational analysis and immunoinformatics approaches include identification of potential conserve epitopes and selection of epitopes based on allergenicity, toxicity, antigenicity, and molecular docking were used for epitope prediction and screening. In the next step, selected segments of the epitopes were attached by the suitable linkers. Finally, Maltese-bound protein (MBP) as an adjuvant was added to the novel vaccine structure. The secondary and third structures of the designed multi-epitope vaccine were predicted via immunoinformatics algorithms. Predicted structure refined and validated for attaining best stability. In the end, immunoinformatics evaluation, molecular docking, and molecular dynamics were performed to confirm vaccine efficiency. Codon optimization and in silico cloning were done to ensure the expression yield of the novel multi-epitope vaccine in the target host. Results: This study showed that our data support the suggestion that the designed vaccine could induce immune responses against SARS-CoV-2 variants. Conclusion: The structure designed had acceptable quality with software reviews. Further in vitro and in vivo experiments are needed to confirm the safety and immunogenicity of the candidate vaccine.http://ijmm.ir/article-1-1390-en.htmlb1.1.7 variantcovid-19immunoinformaticssars-cov-2vaccine |
| spellingShingle | Hassan Dariushnejad Vajihe Ghorbanzadeh Soheila Akbari Pejman Hashemzadeh Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools Iranian Journal of Medical Microbiology b1.1.7 variant covid-19 immunoinformatics sars-cov-2 vaccine |
| title | Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools |
| title_full | Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools |
| title_fullStr | Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools |
| title_full_unstemmed | Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools |
| title_short | Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools |
| title_sort | designing a multi epitope peptide vaccine against covid 19 variants utilizing in silico tools |
| topic | b1.1.7 variant covid-19 immunoinformatics sars-cov-2 vaccine |
| url | http://ijmm.ir/article-1-1390-en.html |
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