Functional and structural characterization of COVID-19 risk-associated exonic SNPs and identification of novel therapeutic sites: An in silico analysis

Abstract

The COVID-19 pandemic has highlighted the critical need for effective therapeutic strategies against viral infections, prompting research on the functional characterization of risk-associated single nucleotide polymorphisms (SNPs). This study aimed to analyze exonic SNPs that influence individual susceptibility to COVID-19 through an in silico approach. Using a comprehensive methodology, SNPs were retrieved from databases such as Science Direct and PubMed, categorized into intronic, exonic, UTR, splice site, and intergenic types, with a focus on exonic SNPs. Functional analyses were performed using various bioinformatics tools to assess the effects of synonymous and non-synonymous SNPs on mRNA structure, protein stability, protein function, and potential therapeutic sites. The results revealed significant insights into the impact of specific SNPs on COVID-19 susceptibility. For example, the synonymous SNP rs12252 of IFITM3 was found to have a moderate impact on mRNA structure and binding affinity for microRNAs, while non-synonymous SNPs exhibited varying degrees of functional consequences, with eight variants predicted to be deleterious (with emphasis on the TYK2 SNP rs34536443 that was predicted to be deleterious in all analyzes). This approach facilitated the identification of novel therapeutic targets. Finally, this research highlights the importance of understanding genetic variations in developing personalized medicine approaches for COVID-19.