دوره 11، شماره 4 - ( 8-1402 )                   جلد 11 شماره 4 صفحات 0-0 | برگشت به فهرست نسخه ها

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Rezaei M, Sabzali S, Satari M, Parhamfar M. Immunoinformatics Vaccine Targeting S1-NTD and HA2 Against SARS-CoV-2 and Influenza. Res Mol Med (RMM) 2023; 11 (4)
URL: http://rmm.mazums.ac.ir/article-1-538-fa.html
Immunoinformatics Vaccine Targeting S1-NTD and HA2 Against SARS-CoV-2 and Influenza. Research in Molecular Medicine. 1402; 11 (4)

URL: http://rmm.mazums.ac.ir/article-1-538-fa.html


چکیده:   (591 مشاهده)
Background: Two of the most challenging viruses for vaccine development are SARS-CoV-2, causing the current COVID-19 pandemic, and influenza virus (H1N1), which spreads annually, causing seasonal epidemics or increasing the pandemic risk.
Materials and Methods: In this study, we analyzed the immunodominant epitope regions in fusion peptides consisting of the Spike_S1_ N-terminal domain from SARS-CoV-2 in frame to hemagglutinin H2 (HA2) gene from influenza A virus (H1N1) and also human IFNɣ gene by two (G4S)3 linkers. A comprehensive analysis based on immunoinformatic has been conducted on prediction servers to predict T- and B-cell epitopes. In silico cloning and expression in pET-28(+) expression vector and vaccine optimization were assessed. The overall model quality was accessed, and the docking or binding affinity of the designed vaccine to the Toll-like receptor 3 was analyzed.
Results: The efficiency of the constructed vaccine confirmed by appropriate expression of the designed vaccine candidate tested by in silico cloning in pET–28(+) vector and codon optimization might increase the production of vaccine candidate into Escherichia coli strain K-12.
Conclusion: In conclusion, we suggest that this fusion peptide would be an attractive design strategy for developing a bivalent vaccine against COVID-19 and influenza as promising vaccine candidates without the need to reformulate or vaccinate each year.
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نوع مطالعه: پژوهشي | موضوع مقاله: ايمونولوژي
انتشار: 1402/8/28

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