ABSTRACT
ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS"CoV"2) has rapidly evolved in the last couple of years. This has created major havoc and concern because it has affected millions of people around the world. The new variants of covid"19 are classified into two types, VOI (variant of interest) and VOC (variant of concern). The major variants of concern (VOCs) have shared mutations in severe acute respiratory syndrome coronavirus 2 (SARS"CoV"2). The spike proteins of the novel coronavirus located mostly on the S1 unit result in a higher transmissibility rate and affect the viral virulence and clinical outcome. The spike protein and other non"structural protein mutations in VOCs may lead to escape the approved vaccinations. Here the VOC mutations i.e., OMICRON VARIANT have been discussed in detail, and the therapeutic strategies to enhance the host immune responses have been proposed. Additionally, a computational approach is proposed to design the drug and vaccine for the variant. The protein structure for the OMICRON variant has been predicted through bioinformatics tools and several databases have been used to identify suitable natural inhibitors. The OMICRON variant was analyzed to identify suitable vaccine candidates by identifying B"Cell epitopes. To design a drug, REPAGLINIDE and ENT"NATEGLINIDE were identified as natural inhibitors based on docking score. To design a vaccine the B"cell epitope i.e., CLIGAEYVNNSYECD was found to the highest antigenicity score. The present study identifies natural inhibitors and potential antigenic Epitopes which may be used as effective drug and vaccine candidates to suppress the novel coronavirus.
ABSTRACT
Background: The recent emergence of viral pneumonia was caused by the novel coronavirus (SARS-Cov-2), which has spread to many countries and threated the global public health.Results: In the current study, we provide a primary evolutionary analysis based on the codon usage patterns of SARS-Cov-2 genome sequences. We employed bioinformatics technologies to measure the nucleotide compositions, the relative synonymous codon usage (RSCU), the codon adaptation index (CAI), and other indices. Our results reflected that there were some similarities of codon usage bias between SARS-Cov-2 and its natural reservoirs, suggesting that SARS-Cov-2 was tended to evolve its codon usage which was comparable to that of its hosts. Additionally, various degree of adaptation to the SARS-Cov-2 host and vector were estimated, even different genes have different codon adaptation to their reservoirs. We further suggested that SARS-Cov-2 isolates were evolving at a rapid substitution rate under their translation selection pressure of their hosts.Conclusions: The findings of the present study will provide help for the understanding of the elements leading to viral evolution and adaptation to reservoirs.