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SARS-CoV-2 and ORF3a: Non-Synonymous Mutations and Polyproline Regions (preprint)
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.03.27.012013
ABSTRACT
The effect of the rapid accumulation of non-synonymous mutations on the pathogenesis of SARS-CoV-2 is not yet known. To predict the impact of non-synonymous mutations and polyproline regions identified in ORF3a on the formation of B-cell epitopes and their role in evading the immune response, nucleotide and protein sequences of 537 available SARS-CoV-2 genomes were analyzed for the presence of non-synonymous mutations and polyproline regions. Mutations were correlated with changes in epitope formation. A total of 19 different non-synonymous amino acids substitutions were detected in ORF3a among 537 SARS-CoV-2 strains. G251V was the most common and identified in 9.9% (n=53) of the strains and was predicted to lead to the loss of a B-cell like epitope in ORF3a. Polyproline regions were detected in two strains (EPI_ISL_410486, France and EPI_ISL_407079, Finland) and affected epitopes formation. The accumulation of non-synonymous mutations and detected polyproline regions in ORF3a of SARS-CoV-2 could be driving the evasion of the host immune response thus favoring viral spread. Rapid mutations accumulating in ORF3a should be closely monitored throughout the COVID-19 pandemic. ImportanceAt the surge of the COVID-19 pandemic and after three months of the identification of SARS-CoV-2 as the disease-causing pathogen, nucleic acid changes due to host-pathogen interactions are insightful into the evolution of this virus. In this paper, we have identified a set of non-synonymous mutations in ORF3a and predicted their impact on B-cell like epitope formation. The accumulation of non-synonymous mutations in ORF3a could be driving protein changes that mediate immune evasion and favoring viral spread.
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Full text: Available Collection: Preprints Database: bioRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: bioRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint