Abstract：
The SARS-CoV-2 targets were evaluated for a set of FDA-approved drugs using a combination of drug repositioning and rigorous computational modeling methodologies such as molecular docking and molecular dynamics (MD) simulations followed by binding free energy calculations. Six FDA-approved drugs including, Ouabain, Digitoxin, Digoxin, Proscillaridin, Salinomycin and Niclosamide with promising anti-SARS-CoV-2 activity were screened in silico against four SARS-CoV-2 proteins-papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), SARS-CoV-2 main protease (Mpro), and adaptor-associated kinase 1 (AAK1)-in an attempt to define their promising targets. The applied computational techniques suggest that all the tested drugs exhibited excellent binding patterns with higher scores and stable complexes compared to the native protein cocrystallized inhibitors. Ouabain was suggested to act as a dual inhibitor for both PLpro and Mpro enzymes, while Digitoxin bonded perfectly to RdRp. In addition, Salinomycin targeted PLpro. Particularly, Niclosamide was found to target AAK1 with greater affinity compared to the reference drug. Our study provides comprehensive molecular-level insights for identifying or designing novel anti-COVID-19 drugs.
摘要：
使用药物重新定位和严格的计算建模方法（例如分子对接和分子动力学（MD）模拟，然后进行结合自由能计算），对一组FDA批准的药物评估了SARS-CoV-2靶标。6种FDA批准的药物，包括,Ouabain,洋地黄毒素,地高辛,Proscillaridin,针对四种SARS-CoV-2蛋白-木瓜蛋白酶样蛋白酶（PLpro），筛选了具有良好抗SARS-CoV-2活性的盐霉素和氯硝柳胺，RNA依赖性RNA聚合酶（RdRp），SARS-CoV-2主要蛋白酶（Mpro），和衔接子相关激酶1（AAK1）-试图定义它们有希望的靶标。应用的计算技术表明，与天然蛋白质共结晶抑制剂相比，所有测试的药物都表现出优异的结合模式，得分更高，复合物稳定。Ouabain被认为是PLpro和Mpro酶的双重抑制剂，而Digitoxin与RdRp完美结合。此外,盐霉素靶向PLpro。特别是,与参考药物相比,发现氯硝柳胺以更高的亲和力靶向AAK1。我们的研究为识别或设计新型抗COVID-19药物提供了全面的分子水平见解。
