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This research group validated the mCSM-PPI2 variant effect prediction algorithm with 26 published ACE2 mutant SARS-CoV S-protein binding assays and discovered it performed well in this closely related system. The binding site was shown to be quite important for maintaining the interaction between the proteins.
Furthermore, by using the Genome Aggregation Consortium Database (gnomAD), they found three missense variants that inhibited the S-protein ACE2 interaction altogether, and one that was promoting such interaction.
The researchers have also performed in silico saturation mutagenesis of the S-protein ACE2 interface and pinpointed an additional 38 missense mutations that could lead to strong inhibition of binding and one more that is likely to enhance binding. In short, the result of the mutations can go either way, although they more often hamper viral binding. The prevalence and significance of protective mutations
A conservative estimate of strongly protective variant prevalence is between 12 and 70 per 100 thousand people; however, there is the possibility that the prevalence is even higher in certain local populations or those underrepresented in gnomAD.
"Aside from ACE2-S affinity, host cell ACE2 expression levels are known to be important for the cellular specificity of SARS-CoV-2, and attention has been directed toward ACE2 expression levels as a potential factor in COVID-19 susceptibility and severity", further explain study authors.
Different epidemiological features are also in line with this research. For example, already perceived gender difference in COVID-19 pandemic ( i.e., men dying more often) may arise from the ACE2's position on the X chromosome, increasing the expression of certain S-protein resistant ACE2 alleles in women (if present).
In any case, this type of saturation mutant predictions can aid in designing a mutant ACE2 with tailored S-protein affinity as a significant step forward when compared to a current recombinant ACE2 that is undergoing clinical trial. Paving the way for genetic medicine
"Our validation of mCSM-PPI2 with experimental data from the closely related SARS-CoV S-ACE2 complex provides direct evidence that this algorithm yields accurate predictions for this complex and calibrates the algorithm's quantitative predictions with observed physical behavior", say study authors.
"Additionally, we have followed up key results with a critical structural inspection of the local environments of the mutant models, and in our judgment, the predictions are in line with the principles established by the original structural and mutagenesis work in this area," they add.
Potential consequences of this research endeavor are prioritizing experimental work into virus-receptor recognition, developing genetic diagnostic risk profiling for COVID-19 sensitivity and severity, enhancing detection and interpretation in future genetic association studies, as well as developing novel therapeutic agents for COVID-19. *Important Notice
bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information. Journal reference: MacGowan, S.A. & Barton, G.J. (2020). Missense variants in ACE2 are predicted to encourage and inhibit interaction with SARS-CoV-2 Spike and contribute to genetic risk in COVID-19. bioRxiv . https://doi.org/10.1101/2020.05.03.074781 .
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