Identification of potential inhibitors of coronavirus SARS-CoV-2 using the methods of virtual screening and molecular modeling

A. Andrianov, Yuri V. Kornoushenko, A. D. Karpenko, A. Tuzikov
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Abstract

To find small-molecule compounds that can simulate the structural and functional properties of the high affinity X77 ligand of the main protease of SARS-CoV-2 - etiologic agent of COVID-19, the virtual screening of 9 molecular libraries of the Pharmit web server containing over 213.5 million chemical structures was performed. Using molecular modeling, the neutralizing activity of the identified molecules was evaluated, resulting in 5 leader compounds promising for synthesis and testing for antiviral activity. The data obtained indicate that these compounds may be used as basic structures for the development of effective drugs to treat the novel coronavirus infection.
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利用虚拟筛选和分子建模方法鉴定冠状病毒SARS-CoV-2的潜在抑制剂
为了寻找能够模拟新冠病毒病原SARS-CoV-2主要蛋白酶高亲和力X77配体结构和功能特性的小分子化合物,对Pharmit web服务器中包含超过2.135亿个化学结构的9个分子文库进行了虚拟筛选。利用分子模型,对鉴定的分子的中和活性进行了评估,得到了5个先导化合物,有望用于合成和抗病毒活性测试。所获得的数据表明,这些化合物可作为开发治疗新型冠状病毒感染的有效药物的基本结构。
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