Virtual screening of molecular databases for potential inhibitors of the NSP16/NSP10 methyltransferase from SARS-CoV-2

COVID-19 is a disease caused by the SARS-CoV-2 virus and represents one of the greatest health problems that humanity faces at the moment. Therefore, efforts have been made with the objective of seeking therapies that could be effective in combating this problematic. In the search for ligands, computational chemistry plays an essential role, since it allows the screening of thousands of molecules on a given target, in order to save time and money for the in vitro or in vivo pharmacological stage. In this paper, we perform a virtual screening by docking looking for potential inhibitors of the NSP16-NSP10 protein dimer (methyltransferase) from SARS-CoV-2, by evaluating a homemade databank of molecules found in plants of the Caatinga Brazilian biome, compounds from ZINC online molecular database, as well as structural analogues of the enzymatic cofactor s-adenosylmethionine (SAM) and a known inhibitor in the literature, sinefungin (SFG), provided at PubChem database. All the evaluated sets presented molecules that deserve attention, highlighting four compounds from ZINC as the most promising ligands. These results contribute to the discovery of new molecular hits, in the search of potential agents against SARS-CoV-2 virus, still unveiling a pathway that can be used in combined therapies.(c) 2022 Elsevier B.V. All rights reserved.

Automated summary

COVID-19 is a significant health problem caused by the SARS-CoV-2 virus. This study utilized computational chemistry to search for potential inhibitors and evaluated various molecular compounds, including those derived from plants in the Brazilian Caatinga biome, the ZINC online molecular database, structural analogues of the enzymatic cofactor S-adenosylmethionine (SAM), and a known inhibitor called sinefungin (SFG). The results identified four compounds from ZINC as the most promising ligands, contributing to the discovery of new molecular hits and potential agents against SARS-CoV-2.