COVID19: Exploring uncommon epitopes for a stable immune response through MHC1 binding
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Abstract
The COVID19 pandemic has resulted in 1,092,342 deaths as of 14 th October 2020, indicating the urgent need for a vaccine. This study highlights novel protein sequences generated by shot gun sequencing protocols that could serve as potential antigens in the development of novel subunit vaccines and through a stringent inclusion criterion, we characterized these protein sequences and predicted their 3D structures. We found distinctly antigenic sequences from the SARS-CoV-2 that have led to identification of 4 proteins that demonstrate an advantageous binding with Human leukocyte antigen-1 molecules. Results show how previously unexplored proteins may serve as better candidates for subunit vaccine development due to their high stability and immunogenicity, reinforce by their HLA-1 binding propensities and low global binding energies. This study thus takes a unique approach towards furthering the development of vaccines by employing multiple consensus strategies involved in immuno-informatics technique.
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SciScore for 10.1101/2020.10.14.339689: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Antigenicity prediction: Antigenicity prediction of the top eight uncharacterized coronavirus proteins selected after 3D molecular models’ validation was performed using VaxiJen tool. VaxiJensuggested: (VaxiJen, RRID:SCR_018514)The top 1000 results from PatchDock were then submitted to FireDock (53) for refinement of protein-protein docking solutions. PatchDocksuggested: (PatchDock, RRID:SCR_017589)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer:…SciScore for 10.1101/2020.10.14.339689: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Antigenicity prediction: Antigenicity prediction of the top eight uncharacterized coronavirus proteins selected after 3D molecular models’ validation was performed using VaxiJen tool. VaxiJensuggested: (VaxiJen, RRID:SCR_018514)The top 1000 results from PatchDock were then submitted to FireDock (53) for refinement of protein-protein docking solutions. PatchDocksuggested: (PatchDock, RRID:SCR_017589)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- No funding statement was detected.
- No protocol registration statement was detected.
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