Evaluation of potential anti-RNA-dependent RNA polymerase (RdRP) drugs against the newly emerged model of COVID-19 RdRP using computational methods.

ABSTRACT

INTRODUCTION: Despite all the efforts to treat COVID-19, no particular cure has been found for this virus. Since developing antiviral drugs is a time-consuming process, the most effective approach is to evaluate the approved and under investigation drugs using in silico methods. Among the different targets within the virus structure, as a vital component in the life cycle of coronaviruses, RNA-dependent RNA polymerase (RdRP) can be a critical target for antiviral drugs. The impact of the existence of RNA in the enzyme structure on the binding affinity of anti-RdRP drugs has not been investigated so far. METHODS: In this study, the potential anti-RdRP effects of a variety of drugs from two databases (Zinc database and DrugBank) were evaluated using molecular docking. For this purpose, the newly emerged model of COVID-19 (RdRP) post-translocated catalytic complex (PDB ID 7BZF) that consists of RNA was chosen as the target. RESULTS: The results indicated that idarubicin (IDR), a member of the anthracycline antibiotic family, and fenoterol (FNT), a known beta-2 adrenergic agonist drug, tightly bind to the target enzyme and could be used as potential anti-RdRP inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These outcomes revealed that due to the ligand-protein interactions, the presence of RNA in this structure could remarkably affect the binding affinity of inhibitor compounds. CONCLUSION: In silico approaches, such as molecular docking, could effectively address the problem of finding appropriate treatment for COVID-19. Our results showed that IDR and FNT have a significant affinity to the RdRP of SARS-CoV-2; therefore, these drugs are remarkable inhibitors of coronaviruses.