Prospecção in silico de novos ligantes contra o SARS-CoV-2

Abstract

SARS-CoV-2, initially circulating in enzootic cycles, eventually spread to humans, triggering a global pandemic declared by the WHO in March 2020. Despite having a prolonged incubation period and a relatively slow evolutionary rate, the virus’s high infectious capacity contributed to its rapid transmission worldwide. Over time, new genomic variants emerged, highlighting the need for continuous monitoring to assess their impact on transmission rates and disease severity. Certain strains have shown partial resistance to vaccines, introducing additional challenges for disease control. In this context, bioinformatics tools, including bioisosterism, molecular docking, and analyses of physicochemical, pharmacokinetic (ADMET), and druggability properties, have become essential in antiviral drug development. These techniques support the identification and optimization of antiviral molecules, as well as the study of molecular interactions to identify energetically stable complexes. This research applied these bioinformatics approaches to define a target molecule and screen ligands with antiviral pharmacological potential against COVID-19. The findings highlighted NSP9 as a receptor with a high degree of conservation. Although it exhibited some "druggability limitations," the receptor-ligand interaction with mycophenolic acid (MPA) showed energetically favorable binding, especially in complex 1b. Additionally, through bioisosterism, an isoster called 1c was generated, demonstrating superior physicochemical and pharmacokinetic properties compared to other bioisosteres. Nevertheless, MPA remained the ligand with the highest antiviral potential among those evaluated. Thus, the research suggests continued investigation of the MPA and 1c compounds, alongside further exploration of additional bioisosterism techniques, with the aim of achieving improved therapeutic outcomes and enhancing the potential for effective treatments against COVID-19.