Systematic structure guided clustering of chemical lead compounds targeting RdRp of SARS-CoV-2

Abstract

BACKGROUND: To combat the global health issue caused by SARS-CoV2, scientists are attempting various therapeutic approaches towards drug discovery including computational biology and drug-repurposing. Recent studies have highlighted the conserved nature of RNA-dependent RNA polymerase (RdRp) of coronaviruses affecting human, bat and animals. In this study attempts have been made to identify the potential inhibitors of RdRp by utilizing molecular docking and MD simulation studies. METHODS: Systematic structure-based screening of chemical compounds from public libraries was performed to identify the potential lead molecules inhibiting RdRp. This structure driven clustering of compounds is based on decision tree model generated by combining two properties: 1) shape descriptors; and 2) critical number of multiple bonds. The enabled screening of potential chemical compounds was subjected to molecular docking followed by molecular dynamics simulation studies. RESULTS: The results revealed that the stability of protein-drug complex structure was in the order of RdRp-Oxoglaucine >RdRp-Flutroline >RdRp-Brucine complex. CONCLUSIONS: This study identifies Oxoglaucine, Brucine and Flutroline as prospective inhibiting agents of SARS-CoV-2 RdRp and further warrants for experimental validation.