Abstract

Objectives: the COVID-19 pandemic triggering acute respiratory syndrome has become a major global health concern. After one year into this pandemic, special therapies for COVID-19 remain an unprecedented challenge to mankind and finding drugs to treat this disease is extremely urgent. The SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) enzyme that regulates viral replication has been examined as a potential therapeutic target for the inhibition of SARS-CoV-2 infection. In this study, the authors evaluated the ability of RNA-dependent RNA polymerase drug inhibitors by using an in silico molecular docking model. Methods: the 3D structure of RdRp enzyme (PDB ID:6M71, resolution of 2.90 Å) was derived from the Protein Data Bank RCSB. The ligand structures were collected from DrugBank for the RdRp target. Molecular docking was done by AutoDock Vina software. Lipinski’s rule of five is used to compare compounds with drug-like and non-drug-like properties. Pharmacokinetic parameters of potential compounds were evaluated using the pkCSM tool. Results: based on the DrugBank database, we collected 192 antiviral molecules and compared them to remdesivir, which has inhibitory activity with this protein target. Results showed that 26 out of 192 compounds have a higher ability to inhibit the SARS-CoV-2 RdRp enzyme than remdesivir. Next, 6 drugs were selected by visually inspecting the docking results with focus on the main interaction between crucial residues at the binding site of the SARS-CoV-2 RdRp enzyme. For the visual inspection, the existence of polar interactions with ASP760 and ASP761 were utilised as the preference criterion. Finally, Lipinski’s rule of 5 criteria and absorption, distribution, metabolism, excretion and toxicity (ADMET) profile analysis suggested five drugs that have good pharmacokinetic properties. Conclusions: these drugs were dihydroergotamine, sofosbuvir, nilotinib, tipranavir, and darunavir and may be used as anti-SARS-CoV-2 agents.

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