Computational investigation of potential inhibitors of novel coronavirus 2019 through structure-based virtual screening, molecular dynamics and density functional theory studies

Abstract

Despite the intensive research efforts towards antiviral drug against COVID-19, no potential drug or vaccines has not yet discovered. Initially, the binding site of COVID-19 main protease was predicted which located between regions 2 and 3. Structure-based virtual screening was performed through a hierarchal mode of elimination technique after generating a grid box. This led to the identification of five top hit molecules that were selected on the basis of docking score and visualization of non-bonding interactions. The docking results revealed that the hydrogen bonding and hydrophobic interactions are the major contributing factors in the stabilization of complexes. The docking scores were found between -7.524 and -6.711 kcal/mol indicating strong ligand-protein interactions. Amino acid residues Phe140, Leu141, Gly143, Asn142, Thr26, Glu166 and Thr190 (hydrogen bonding interactions) and Phe140, Cys145, Cys44, Met49, Leu167, Pro168, Met165, Val42, Leu27 and Ala191 (hydrophobic interactions) formed the binding pocket of COVID-19 main protease. From identified hits, ZINC13144609 and ZINC01581128 were selected for atomistic MD simulation and density functional theory calculations. MD simulation results confirm that the protein interacting with both hit molecules is stabilized in the chosen POPC lipid bilayer membrane. The presence of lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) in the hydrophobic region of the hit molecules leads to favorable ligand-protein contacts. The calculated pharmacokinetic descriptors were found to be in their acceptable range and therefore confirming their drug-like properties. Hence, the present investigation can serve as the basis for designing and developing COVID-19 inhibitors. Communicated by Ramaswamy H. Sarma.