Virtual screening, ADMET prediction and dynamics simulation of potential compounds targeting the main protease of SARS-CoV-2

针对SARS-CoV-2主要蛋白酶的潜在化合物的虚拟筛选、ADMET预测和动力学模拟

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Abstract

The coronavirus disease-2019 caused by a novel SARS CoV-2 virus has emerged as a global threat. Still, no drugs are available for its treatment. The main protease is the most conserved structure responsible for the posttranslational processing of non-structural polyproteins of this virus. Therefore, it can be the potential target for drug discovery against SARS CoV-2. Twenty-one thousand two hundred and seven chemical compounds used for sequential virtual screening studies including coronavirus screening compounds (Life Chemical database) and antiviral compounds (Asinex database). The Schrodinger suite 2019 employed for high throughput screening, molecular docking and MM-GBSA through the Glide module. Subsequently, 23 compounds were selected in the phase first selection criteria for re-docking with AutoDock and iDock followed by ADMET prediction. The drug-likeness predicted through Lipinski's rule of five, Veber's rule and Muegge's rule. Finally, three ligands were selected for molecular dynamics simulation studies over 150 ns against the main protease of the SARS CoV-2. They showed promising docking scores on Glide, iDock and AutoDock Vina algorithms (ligand F2679-0163: -10.75, -10.29 and -9.2; ligand F6355-0442: -9.38, -8.61 and -7.6; ligand 8250: -9.795, -7.94 and -7.5), respectively. The RMSD parameter remained stable at 2.5 Å for all the three ligands for 150 ns. The high RMSF fluctuations, RoG of around 22 Å and the binding free energy were favorable in each case. The hydrogen bond interactions of 8250, F6355-0442 and F2679-0163 were six, five and three, respectively. These compounds can be further explored for in vitro experimental validation against SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

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