Antiviral Resistance against Viral Mutation: Praxis and Policy for SARS-CoV-2
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Abstract
New tools developed by Moderna, BioNTech/Pfizer, and Oxford/Astrazeneca, among others, provide universal solutions to previously problematic aspects of drug or vaccine delivery, uptake and toxicity, portending new tools across the medical sciences. A novel method is presented based on estimating protein backbone free energy via geometry to predict effective antiviral targets, antigens and vaccine cargos that are resistant to viral mutation. This method, partly described in earlier work of the author, is reviewed and reformulated here in light of the recent proliferation of structural data on the SARS-CoV-2 spike glycoprotein and its latest mutations in the variants of concern and several further variants of interest including all international lineages. Particular attention to structures computed with Cryo Electron Microscopy allows the novel approach of probing the pH dependence of free energy in order to infer function. Key findings include: collections of recurring mutagenic residues occur across strains, presumably through cooperative convergent evolution; the preponderance of mutagenic residues do not participate in backbone hydrogen bonds; metastability of the spike glycoprotein limits the change of free energy from before to after mutation and thereby constrains selective pressure; and there are mRNA or virus-vector cargos which target low free energy peptides proximal to conserved high free energy peptides providing specific recipes for vaccines with greater specificity than the current full-spike approach. These results serve to limit peptides in the spike glycoprotein with high mutagenic potential and thereby provide a priori constraints on viral and attendant vaccine evolution. Scientific and regulatory challenges to nucleic acid therapeutic and vaccine development and deployment are finally discussed.
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SciScore for 10.1101/2021.02.25.432861: (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
No key resources detected.
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 …
SciScore for 10.1101/2021.02.25.432861: (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
No key resources detected.
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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