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ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

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Research Article

A Computational Approach for Designing and Validating Small Interfering RNA against SARS-CoV-2 Variants

Author(s): Kishore Dhotre, Debashree Dass, Anwesha Banerjee, Vijay Nema and Anupam Mukherjee*

Volume 20, Issue 6, 2024

Published on: 14 September, 2023

Page: [876 - 887] Pages: 12

DOI: 10.2174/1573409920666230825111406

Price: $65

Abstract

Aims: The aim of this study is to develop a novel antiviral strategy capable of efficiently targeting a broad set of SARS-CoV-2 variants.

Background: Since the first emergence of SARS-CoV-2, it has rapidly transformed into a global pandemic, posing an unprecedented threat to public health. SARS-CoV-2 is prone to mutation and continues to evolve, leading to the emergence of new variants capable of escaping immune protection achieved due to previous SARS-CoV-2 infections or by vaccination.

Objective: RNA interference (RNAi) is a remarkable biological mechanism that can induce gene silencing by targeting complementary mRNA and inhibiting its translation.

Methods: In this study, using the computational approach, we predicted the most efficient siRNA capable of inhibiting SARS-CoV-2 variants of concern (VoCs).

Results: The presented siRNA was characterized and evaluated for its thermodynamic properties, offsite-target hits, and in silico validation by molecular docking and molecular dynamics simulations (MD) with Human AGO2 protein.

Conclusion: The study contributes to the possibility of designing and developing an effective response strategy against existing variants of concerns and preventing further.

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