Potential inhibitors targeting SARS-CoV-2 proteins probed by in silico methods

Abstract

In late 2019, a new coronavirus was identified as the cause of a set of pneumonia cases in Wuhan, a city in China's Hubei province, later denominated COVID-19, which means coronavirus disease 2019. The virus that causes COVID-19 is called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Important viral enzymes, such as the main protease (Mpro) and RNA polymerase (RdRp) are important therapeutic targets for the treatment of COVID-19. In this sense, this thesis aims to use computational approaches, which can effectively contribute to the discovery and rational development of new therapies, mainly through the drug repositioning. To carry out these works, we used several computational techniques, employing methods of quantum mechanics and molecular mechanics, to evaluate the interaction modes of the compounds in the active site of the molecular targets. Our quinoline oxide nitroderivative compounds showed to be good inhibitors of the viral enzyme Mpro, according to our theoretical results, being promising for further experimental studies. Our results also suggest that the drug combination is effective due to their increased functional properties, providing an innovative way to connect structural changes with electron transfer kinetics. Several repositioned drugs and derivatives were evaluated for their inhibitory properties, whose affinity results suggest that these compounds are potential inhibitors of Mpro and RdRp. Finally, the interaction modes of these drugs were also investigated, as well as the interaction modes of their fragments in the study of metabolism. These studies showed that these drugs can generate metabolite fragments with different reactivity and toxicity.