Department of Chemistry, King Fahd University of Petroleum and Minerals, Dhahran, 31261 Saudi Arabia.
Department of Chemistry, University of Saskatchewan, 110 Science Place, Saskatoon, Saskatchewan S7N 5C9, Canada.
Virus Res. 2020 Aug;285:198022. doi: 10.1016/j.virusres.2020.198022. Epub 2020 May 15.
The recent outbreak of the deadly COVID-19 disease, being caused by the novel coronavirus (SARS-CoV-2), has put the world on red alert as it keeps spreading and recording more fatalities. Research efforts are being carried out to curtail the disease from spreading as it has been declared as of global health emergency. Hence, there is an exigent need to identify and design drugs that are capable of curing the infection and hinder its continual spread across the globe. Herein, a computer-aided drug design tool known as the virtual screening method was used to screen a database of 44 million compounds to find compounds that have the potential to inhibit the surface glycoprotein responsible for virus entry and binding. The consensus scoring approach selected three compounds with promising physicochemical properties and favorable molecular interactions with the target protein. These selected compounds can undergo lead optimization to be further developed as drugs that can be used in treating the COVID-19 disease.
最近由新型冠状病毒(SARS-CoV-2)引起的致命 COVID-19 疾病爆发,使世界处于红色警戒状态,因为它仍在继续传播并记录更多的死亡人数。正在开展研究工作以遏制这种疾病的传播,因为它已被宣布为全球卫生紧急事件。因此,迫切需要确定和设计能够治愈感染并阻止其在全球范围内持续传播的药物。在这里,使用了一种称为虚拟筛选方法的计算机辅助药物设计工具来筛选一个包含 4400 万个化合物的数据库,以寻找具有抑制负责病毒进入和结合的表面糖蛋白的潜力的化合物。共识评分方法选择了三种具有有前途的物理化学性质和与目标蛋白有利的分子相互作用的化合物。这些选定的化合物可以进行先导优化,以进一步开发可用于治疗 COVID-19 疾病的药物。