背景:自2019年12月COVID-19爆发以来,它发展成为影响全球所有国家和数百万人的大流行。直到现在,没有药物可以控制病毒传播。作为药物发现的辅助,分子对接和分子动力学工具得到广泛应用。计算机模拟研究使快速筛选潜在分子成为可能,这些分子可能是针对目标蛋白质的抑制剂/药物。作为我们药物发现研究的延续,我们用SARS-CoV-2,RNA依赖性RNA聚合酶(RdRp)对我们报道的12种非天然核苷和14种设计者Avigan类似物进行了分子对接研究,我们想在这里报告。也进行了同样的计算,取11个已知/低于试验/商业核苷药物分子,比较RdRp催化位点的结合相互作用。我们报道的核苷和设计者核苷的对接结果和结合效率与市售药物如remdesevir和favipiravir的结合能进行了比较。此外,我们通过分子动力学研究(MD)评估了最佳对接分子的蛋白质-药物结合效率和稳定性。从我们的研究来看,我们发现,我们提出的药物很少在SARS-CoV-2RdRp的催化袋中显示出有希望的结合效率,并且可以成为有希望的RdRp抑制剂药物候选物。因此,这项研究对于在开发成功的核苷类药物方面取得进展以及在湿实验室进行抗病毒试验以了解其对COVID-19的疗效将具有重要意义.
方法:所有对接研究均使用AutoDock4.2、AutoDockVina和MolegroVirtualDocker进行。在对接研究之后,MD模拟是按照GROMACSver的标准协议进行的.2019.6.通过应用CHARMM36全原子生物分子力场。使用BioviaDiscoveryStudio套件研究了药物-蛋白质相互作用,Ligplot软件,和蛋白质-配体相互作用分析器(PLIP)。
BACKGROUND: Since the outbreak of COVID-19 in December 2019, it developed into a pandemic affecting all the countries and millions of people around the globe. Until now, there is no medicine available to contain the spread of the virus. As an aid to drug discovery, the molecular docking and molecular dynamic tools were applied extensively. In silico studies made it possible for rapid screening of potential molecules as possible inhibitors/drugs against the targeted proteins. As a continuation of our drug discovery research, we have carried out molecular docking studies of our 12 reported unnatural
nucleosides and 14 designer Avigan analogs with SARS-CoV-2, RNA-dependent RNA polymerase (RdRp), which we want to report herein. The same calculation was also carried out, taking 11 known/under trail/commercial nucleoside drug molecules for a comparison of the binding interactions in the catalytic site of RdRp. The docking results and binding efficiencies of our reported
nucleosides and designer nucleosidic were compared with the binding energy of commercially available drugs such as remdesevir and favipiravir. Furthermore, we evaluated the protein-drug binding efficiency and stability of the best docked molecules by molecular dynamic studies (MD). From our
study, we have found that few of our proposed drugs show promising binding efficiency at the catalytic pocket of SARS-CoV-2 RdRp and can be a promising RdRp inhibitor drug candidate. Hence, this
study will be of importance to make progress toward developing successful nucleoside-based drugs and conduct the antiviral test in the wet lab to understand their efficacy against COVID-19.
METHODS: All the docking studies were carried out with AutoDock 4.2, AutoDock Vina and Molegro Virtual Docker. Following the docking studies, the MD simulations were carried out following the standard protocol with the GROMACS ver. 2019.6. by applying the CHARMM36 all-atom biomolecular force field. The drug-protein interaction was studied using the Biovia Discovery Studio suite, Ligplot software, and Protein-Ligand Interaction Profiler (PLIP).