Department of Radiopharmacy and Pharmaceutical Chemistry, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Department of Medicinal Chemistry, Faculty of Pharmacy, Alborz University of Medical Sciences, Karaj, Iran.
J Biomol Struct Dyn. 2022 Sep;40(14):6569-6586. doi: 10.1080/07391102.2021.1886991. Epub 2021 Feb 18.
The outbreak of the second severe acute respiratory syndrome coronavirus (SARS-CoV-2) known as COVID-19 has caused global concern. No effective vaccine or treatment to control the virus has been approved yet. Social distancing and precautionary protocols are still the only way to prevent person-to-person transmission. We hope to identify anti-COVID-19 activity of the existing drugs to overcome this pandemic as soon as possible. The present study used HEX and AutoDock Vina softwares to predict the affinity of about 100 medicinal structures toward the active site of 3-chymotrypsin-like protease (3Clpro) and RNA-dependent RNA polymerase (RdRp), separately. Afterwards, MOE software and the pharmacophore-derived query methodology were employed to determine the pharmacophore model of their inhibitors. Tegobuvir () and compound showed the best binding affinity toward RdRp and 3Clpro of SARS-CoV-2 in silico, respectively. Tegobuvir -previously applied for hepatitis C virus- formed highly stable complex with uncommon binding pocket of RdRp (E total: -707.91 Kcal/mol) in silico. In addition to compound , tipranavir () and atazanavir () as FDA-approved HIV protease inhibitors were tightly interacted with the active site of SARS-CoV-2 main protease as well. Based on pharmacophore modelling, a good structural pattern for potent candidates against SARS-CoV-2 main enzymes is suggested. Re-tasking or taking inspiration from the structures of tegobuvir and tipranavir can be a proper approach toward coping with the COVID-19 in the shortest possible time and at the lowest cost.Communicated by Ramaswamy H. Sarma.
新型严重急性呼吸系统综合症冠状病毒（SARS-CoV-2）爆发，即 COVID-19，引起了全球关注。目前尚未批准任何有效的疫苗或治疗方法来控制该病毒。社交距离和预防措施仍然是预防人际传播的唯一方法。我们希望尽快确定现有药物的抗 COVID-19 活性，以克服这一大流行病。本研究使用 HEX 和 AutoDock Vina 软件分别预测约 100 种药物结构对 3 肽酰基肽水解酶（3Clpro）和 RNA 依赖性 RNA 聚合酶（RdRp）活性部位的亲和力。然后，使用 MOE 软件和基于药效团的查询方法来确定其抑制剂的药效团模型。替诺福韦（）和化合物在计算机模拟中分别对 SARS-CoV-2 的 RdRp 和 3Clpro 表现出最佳的结合亲和力。替诺福韦-以前用于丙型肝炎病毒-在计算机模拟中与 RdRp 的不常见结合口袋（E 总：-707.91 Kcal/mol）形成高度稳定的复合物。除了化合物，作为 FDA 批准的 HIV 蛋白酶抑制剂的替普那韦（）和阿扎那韦（）也与 SARS-CoV-2 主要蛋白酶的活性部位紧密相互作用。基于药效团建模，建议了针对 SARS-CoV-2 主要酶的有效候选药物的良好结构模式。从替诺福韦和替普那韦的结构中重新设计或获得灵感可以是在最短的时间内以最低的成本应对 COVID-19 的一种恰当方法。由 Ramaswamy H. Sarma 传达。
