Paper Title
Computational Prediction of siRNA as a Potential Antiviral Agent against COVID-19

Abstract
Severe acute respiratory syndrome coronavirus 2, also known as COVID-19, has become a public safety issue. It had first originated in Wuhan, China, about December 2019, and later spread to approximately 222 countries owing to its extremely infectious nature. Numerous vaccines have previously been licensed by various authorities across the world to develop herd immunity in the population.In line with these efforts, RNA interference (RNAi) technology offers the possibility of stepping up the fight against this virus. RNA interference (RNAi) is a novel regulatory and efficient silencing strategy in molecular therapy via a sequence-specific RNA degradation mechanism. Several studies revealed the effectiveness of siRNAs inhibiting viral replication. In this study, computational tools were used to develop specific siRNA molecules against the spike glycoprotein gene, which encode an important protein that facilitating virus entry into the host cell. Through a strict filtering process, four siRNAs molecules were selected with the best possible activity. Through a strict filtering process, four siRNAs molecules were selected with the best possible activity. These predicted siRNAs should effectively silence the targeted gene. The siRNA-based approach aims to reduce the time and effort required by conventional trials and wet-lab methods that can be prone to errors, and has the potential to serve as a decent basis for future researchers to develop a successful RNAi therapeutic. Keywords - Severe acute respiratory syndrome, siRNA Design, Gene Silencing, Spike Glycoprotein.