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

IF 1.5 4区医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2024-01-01 DOI:10.2174/1573409920666230825111406

Kishore Dhotre, Debashree Dass, Anwesha Banerjee, Vijay Nema, Anupam Mukherjee

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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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设计和验证抗 SARS-CoV-2 变异小干扰 RNA 的计算方法

目的：本研究旨在开发一种新型抗病毒策略，该策略能够有效地针对多种 SARS-CoV-2 变体：背景：自 SARS-CoV-2 首次出现以来，它已迅速转变为一种全球性流行病，对公共健康构成了前所未有的威胁。SARS-CoV-2容易发生变异并不断进化，从而导致新变种的出现，这些新变种能够躲过因以前感染过SARS-CoV-2或接种过疫苗而获得的免疫保护：RNA干扰（RNAi）是一种显著的生物学机制，它可以通过靶向互补的mRNA并抑制其翻译来诱导基因沉默：在这项研究中，我们利用计算方法预测了能够抑制 SARS-CoV-2 变异株（VoCs）的最有效 siRNA：结果：我们对所提出的 siRNA 进行了表征，并评估了其热力学特性、非位点靶标命中率，还通过与人类 AGO2 蛋白的分子对接和分子动力学模拟（MD）对其进行了硅学验证：这项研究有助于设计和开发有效的应对策略，以解决现有的变异问题，并防止进一步恶化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Current computer-aided drug design 医学-计算机：跨学科应用

CiteScore

3.70

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.