Department of Biotechnology, Institute of Biotechnology, College of Life and Applied Sciences, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Republic of Korea.
Centre for Bioinformatics, Computational and Systems Biology, Pathfinder Research and Training Foundation, Greater Noida, India.
Life Sci. 2020 Sep 15;257:118080. doi: 10.1016/j.lfs.2020.118080. Epub 2020 Jul 9.
The COVID-19 pandemic raised by SARS-CoV-2 is a public health emergency. However, lack of antiviral drugs and vaccine against human coronaviruses demands a concerted approach to challenge the SARS-CoV-2 infection. Under limited resource and urgency, combinatorial computational approaches to identify the potential inhibitor from known drugs could be applied against risen COVID-19 pandemic. Thereof, this study attempted to purpose the potent inhibitors from the approved drug pool against SARS-CoV-2 main protease (M). To circumvent the issue of lead compound from available drugs as antivirals, antibiotics with broad spectrum of viral activity, i.e. doxycycline, tetracycline, demeclocycline, and minocycline were chosen for molecular simulation analysis against native ligand N3 inhibitor in SARS-CoV-2 M crystal structure. Molecular docking simulation predicted the docking score >-7 kcal/mol with significant intermolecular interaction at the catalytic dyad (His41 and Cys145) and other essential substrate binding residues of SARS-CoV-2 M. The best ligand conformations were further studied for complex stability and intermolecular interaction profiling with respect to time under 100 ns classical molecular dynamics simulation, established the significant stability and interactions of selected antibiotics by comparison to N3 inhibitor. Based on combinatorial molecular simulation analysis, doxycycline and minocycline were selected as potent inhibitor against SARS-CoV-2 M which can used in combinational therapy against SARS-CoV-2 infection.
由 SARS-CoV-2 引起的 COVID-19 大流行是一场公共卫生紧急事件。然而,由于缺乏针对人类冠状病毒的抗病毒药物和疫苗,因此需要采取协同方法来应对 SARS-CoV-2 感染。在资源有限且紧迫的情况下,可以应用组合计算方法从已知药物中鉴定出针对 COVID-19 大流行的潜在抑制剂。因此,本研究试图从已批准药物库中寻找针对 SARS-CoV-2 主蛋白酶 (M) 的有效抑制剂。为了避免从现有药物中寻找先导化合物作为抗病毒药物的问题,选择了具有广谱抗病毒活性的抗生素,即强力霉素、四环素、去甲金霉素和米诺环素,用于对 SARS-CoV-2 M 晶体结构中天然配体 N3 抑制剂进行分子模拟分析。分子对接模拟预测对接评分>-7 kcal/mol,与 SARS-CoV-2 M 的催化双原子(His41 和 Cys145)和其他必需的底物结合残基具有显著的分子间相互作用。进一步对最佳配体构象进行了 100 ns 经典分子动力学模拟的复合物稳定性和分子间相互作用分析,与 N3 抑制剂相比,确定了所选抗生素的显著稳定性和相互作用。基于组合分子模拟分析,强力霉素和米诺环素被选为针对 SARS-CoV-2 M 的有效抑制剂,可用于针对 SARS-CoV-2 感染的联合治疗。