Abstract

Computer-aided drug design has been taking an increasing role in the field of modern drug discovery. These in silico computational methods are cost-effective, reduce the use of animal models in pharmacological research, and can be used to study pathogenic organisms without the need for any facilities. Based on the structure of known anti-viral agents, a total of 812 ligands have been designed. All ligands were screened for drug-likeness based on Lipinski rule of five. A database of ligands was constructed and in silico docking analyses were performed using MOE 2015.10 program against three selected viruses, viz., Zika virus, Hepatitis C virus and SARS-CoV-2 virus. Ligand 93 (-8.4469 kcal/mol) and ligand 123 (-8.3609 kcal/mol) were identified to be having higher docking scores as compared to the native ligand 6T8 (-8.2839 kcal/mol) and could be considered potential candidates for further studies in anti-viral drugs against Zika virus. Ligands 153 (-10.3108 kcal/mol), 63 (-9.9968 kcal/mol), 621 (-9.8700 kcal/mol), 31 (-9.5001 kcal/mol) and 779 (-9.3874 kcal/com) were identified as the top five binding ligands, and have docking scores much higher than the reference native ligand K4J (-8.9037 kcal/com). All these ligands can be potent candidates for anti-viral research against Hepatitis C virus. Ligand 798 (-8.0957 kcal/com) and ligand 63 (-8.0778 kcal/com) have higher docking scores as compared to the reference native ligand X77 (-8.0689 kcal/mol), they also interact with the catalytic dyad at the active site of the target protein and can be considered as possible candidates for studies in anti-viral drugs against SARS-CoV-2.
 Keywords: Computer-aided drug design, ADME, Molecular Docking analyses, anti-viral agents, Sars-CoV-2 virus, Zika virus, Hepatitis C virus

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