Theoretical insights into the effect of halogenated substituent on the electronic structure and spectroscopic properties of the favipiravir tautomeric forms and its implications for the treatment of COVID-19.

In this study, we systematically investigated the electronic structure, spectroscopic (nuclear magnetic resonance, infrared, Raman, electron ionization mass spectrometry, UV-Vis, circular dichroism, and emission) properties, and tautomerism of halogenated favipiravir compounds (fluorine, chlorine, and bromine) from a computational perspective. Additionally, the effects of hydration on the proton transfer mechanism of the tautomeric forms of the halogenated favipiravir compounds are discussed. Our results suggest that spectroscopic properties allow for the elucidation of such tautomeric forms. As is well-known, the favipiravir compound has excellent antiviral properties and hence was recently tested for the treatment of new coronavirus (SARS-CoV-2). Through in silico modeling, in the current study, we evaluate the role of such tautomeric forms in order to consider the effect of drug-metabolism in the inhibition process of the main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 virus. According to the molecular docking, all halogenated compounds presented a better interaction energy than the co-crystallized active ligand (-3.5 kcal mol-1) in the viral RdRp, in both wild-type (-6.3 to -6.5 kcal mol-1) and variant (-5.4 to -5.6 kcal mol-1) models. The variant analyzed for RdRp (Y176C) decreases the affinity of the keto form of the compounds in the active site, and prevented the ligands from interacting with RNA. These findings clearly indicated that all these compounds are promising as drug candidates for this molecular target.

Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective.

Understanding the effects of metabolism on the rational design of novel and more effective drugs is still a considerable challenge. To the best of our knowledge, there are no entirely computational strategies that make it possible to predict these effects. From this perspective, the development of such methodologies could contribute to significantly reduce the side effects of medicines, leading to the emergence of more effective and safer drugs. Thereby, in this study, our strategy is based on simulating the electron ionization mass spectrometry (EI-MS) fragmentation of the drug molecules and combined with molecular docking and ADMET models in two different situations. In the first model, the drug is docked without considering the possible metabolic effects. In the second model, each of the intermediates from the EI-MS results is docked, and metabolism occurs before the drug accesses the biological target. As a proof of concept, in this work, we investigate the main antiviral drugs used in clinical research to treat COVID-19. As a result, our strategy made it possible to assess the biological activity and toxicity of all potential by-products. We believed that our findings provide new chemical insights that can benefit the rational development of novel drugs in the future.