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Abdul Mannan Baig
Department of Biological and Biomedical Sciences, Aga Khan University
Corresponding Author
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With over 75762 patients infected and 2130 deaths been reported, the mortality and morbidity caused by the recent outbreak COVID-19 infections are proving colossal when compared to similar epidemics caused by SARS and MERS variant of coronavirus in the past. It was aimed to identify a receptor-binding domain (RBD) in surface glycoprotein (sGP) of COVID-19 and predict epitopes that are capable of interacting with major histocompatibility complex (MHC) alleles to evoke antibody production in vivo. Bioinformatic computational tools were used to analyze the well-studied sGP and the RBD in SARS-CoV and compare it with their homologs in COVID-19. In silico methods that predict epitopes capable of binding MHC allele were used to identify sequences in RDB of sGP in COVID-19 with the intention of discovering sequences that can be used for vaccination and production of monoclonal antibody (mAbs) against COVID-19. The results indicate that COVID-19 has a conserved RBD in the sGP with differences in its sequences that can be exploited for vaccination and manufacturing of specific antibodies against this variant of coronavirus. Reported are 10 sequences of epitopes that are predicted to bind the MHC class I and class II alleles and that do not cross-react with human proteins. Testing in vitro and in animal models can accelerate the translational utility of vaccinating and efficacy of mAbs against the COVID-19 virus.
Keywords
2019-nCoV, COVID-19, Wuhan coronavirus outbreak, viral pandemics, SARS virus, MERS virus, Bat virus, Zoonotic infections, Biological agents, BSL 4
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A new preprint design is coming!
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Abdul Mannan Baig
Department of Biological and Biomedical Sciences, Aga Khan University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 25 Mar, 2020
Community comments: 1
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Bioinformatics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
With over 75762 patients infected and 2130 deaths been reported, the mortality and morbidity caused by the recent outbreak COVID-19 infections are proving colossal when compared to similar epidemics caused by SARS and MERS variant of coronavirus in the past. It was aimed to identify a receptor-binding domain (RBD) in surface glycoprotein (sGP) of COVID-19 and predict epitopes that are capable of interacting with major histocompatibility complex (MHC) alleles to evoke antibody production in vivo. Bioinformatic computational tools were used to analyze the well-studied sGP and the RBD in SARS-CoV and compare it with their homologs in COVID-19. In silico methods that predict epitopes capable of binding MHC allele were used to identify sequences in RDB of sGP in COVID-19 with the intention of discovering sequences that can be used for vaccination and production of monoclonal antibody (mAbs) against COVID-19. The results indicate that COVID-19 has a conserved RBD in the sGP with differences in its sequences that can be exploited for vaccination and manufacturing of specific antibodies against this variant of coronavirus. Reported are 10 sequences of epitopes that are predicted to bind the MHC class I and class II alleles and that do not cross-react with human proteins. Testing in vitro and in animal models can accelerate the translational utility of vaccinating and efficacy of mAbs against the COVID-19 virus.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
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