Department of Bio-Technology, Vignan's Foundation for Science, Technology & Research, Vadlamudi, 522213, Andhra Pradesh, India.
Division of Life Science, Department of Bio & Medical Big Data (BK4 Program), Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-daero, Jinju 52828, Republic of Korea.
J Pharm Sci. 2021 Jun;110(6):2346-2354. doi: 10.1016/j.xphs.2021.03.004. Epub 2021 Mar 5.
The novel coronavirus (SARS-CoV-2) outbreak has started taking away the millions of lives worldwide. Identification of known and approved drugs against novel coronavirus disease (COVID-19) seems to be an urgent need for the repurposing of the existing drugs. So, here we examined a safe strategy of using approved drugs of SuperDRUG2 database against modeled membrane protein (M-protein) of SARS-CoV-2 which is essential for virus assembly by using molecular docking-based virtual screening. A total of 3639 drugs from SuperDRUG2 database and additionally 14 potential drugs reported against COVID-19 proteins were selected. Molecular docking analyses revealed that nine drugs can bind the active site of M-protein with desirable molecular interactions. We therefore applied molecular dynamics simulations and binding free energy calculation using MM-PBSA to analyze the stability of the compounds. The complexes of M-protein with the selected drugs were simulated for 50 ns and ranked according to their binding free energies. The binding mode of the drugs with M-protein was analyzed and it was observed that Colchicine, Remdesivir, Bafilomycin A1 from COVID-19 suggested drugs and Temozolomide from SuperDRUG2 database displayed desirable molecular interactions and higher binding affinity towards M-protein. Interestingly, Colchicine was found as the top most binder among tested drugs against M-protein. We therefore additionally identified four Colchicine derivatives which can bind efficiently with M-protein and have better pharmacokinetic properties. We recommend that these drugs can be tested further through in vitro studies against SARS-CoV-2 M-protein.
新型冠状病毒(SARS-CoV-2)的爆发已在全球夺走了数百万人的生命。寻找针对新型冠状病毒病(COVID-19)的已知和已批准的药物似乎是重新利用现有药物的当务之急。因此,在这里,我们通过基于分子对接的虚拟筛选,研究了使用 SuperDRUG2 数据库中已批准的药物针对 SARS-CoV-2 模型膜蛋白(M 蛋白)的安全策略,该蛋白对于病毒组装至关重要。从 SuperDRUG2 数据库中选择了 3639 种药物,另外还选择了 14 种针对 COVID-19 蛋白的潜在药物。分子对接分析表明,有 9 种药物可以与 M 蛋白的活性位点结合,并具有理想的分子相互作用。因此,我们应用分子动力学模拟和 MM-PBSA 结合自由能计算来分析化合物的稳定性。将 M 蛋白与所选药物的复合物模拟 50ns,并根据它们的结合自由能进行排序。分析了药物与 M 蛋白的结合模式,观察到来自 COVID-19 建议药物的秋水仙碱、瑞德西韦和巴佛洛霉素 A1 以及来自 SuperDRUG2 数据库的替莫唑胺与 M 蛋白显示出理想的分子相互作用和更高的亲和力。有趣的是,秋水仙碱被发现是针对 M 蛋白的测试药物中结合能力最强的药物。因此,我们另外鉴定了四种可有效与 M 蛋白结合且具有更好药代动力学性质的秋水仙碱衍生物。我们建议进一步通过针对 SARS-CoV-2 M 蛋白的体外研究来测试这些药物。