Department of Pharmacology, Post Graduate Institute of Medical Education and Reseasrch (PGIMER), Chandigarh, 160012, India.
Pharmacol Rep. 2021 Jun;73(3):736-749. doi: 10.1007/s43440-020-00195-y. Epub 2021 Jan 3.
COVID-19 cases are on surge; however, there is no efficient treatment or vaccine that can be used for its management. Numerous clinical trials are being reviewed for use of different drugs, biologics, and vaccines in COVID-19. A much empirical approach will be to repurpose existing drugs for which pharmacokinetic and safety data are available, because this will facilitate the process of drug development. The article discusses the evidence available for the use of Ivermectin, an anti-parasitic drug with antiviral properties, in COVID-19.
A rational review of the drugs was carried out utilizing their clinically significant attributes. A more thorough understanding was met by virtual embodiment of the drug structure and realizable viral targets using artificial intelligence (AI)-based and molecular dynamics (MD)-simulation-based study.
Certain studies have highlighted the significance of ivermectin in COVID-19; however, it requires evidences from more Randomised Controlled Trials (RCTs) and dose- response studies to support its use. In silico-based analysis of ivermectin's molecular interaction specificity using AI and classical mechanics simulation-based methods indicates positive interaction of ivermectin with viral protein targets, which is leading for SARS-CoV 2 N-protein NTD (nucleocapsid protein N-terminal domain).
COVID-19 病例正在激增;然而,目前尚无有效的治疗方法或疫苗可用于治疗。正在对大量临床试验进行审查,以评估不同药物、生物制剂和疫苗在 COVID-19 中的应用。一种更具经验性的方法是重新利用现有的药物,这些药物具有药代动力学和安全性数据,因为这将有助于药物开发过程。本文讨论了伊维菌素(一种具有抗病毒特性的抗寄生虫药物)在 COVID-19 中的应用的现有证据。
利用药物的临床显著属性对药物进行了合理的审查。通过使用人工智能 (AI) 和分子动力学 (MD) 模拟为基础的研究对药物结构和可实现的病毒靶标进行虚拟体现,从而获得了更深入的理解。
某些研究强调了伊维菌素在 COVID-19 中的重要性;然而,需要更多的随机对照试验(RCT)和剂量反应研究来支持其使用。使用人工智能和基于经典力学模拟的方法对伊维菌素的分子相互作用特异性进行基于计算机的分析表明,伊维菌素与病毒蛋白靶标具有积极的相互作用,这对于 SARS-CoV 2 N 蛋白 NTD(核衣壳蛋白 N 端结构域)来说是一个积极的结果。