Resumen:
At the end of 2019, SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) was
the cause of unknown pneumonia, but soon after, it was portrayed as coronavirus 2019
(COVID-19). COVID-19 is an ongoing global pandemic that has claimed and threatened many
lives worldwide. Before developing immune agents to combat SARS-CoV-2, potential
screenings with numerous known drugs were previously carried out. Still, the efficacy to
combat the critical problems was not satisfactory. Soon after, due to its potential for replication
and infection, SARS-CoV-2 presented new variants, the result of an accumulation of mutations
in the sequence and structure of the Spike (S) glycoprotein, which is by far the most critical
protein for SARS-CoV-2. This protein participates directly in the replication of SARS-CoV-2
infection, pathogenicity, transmission, and evolution. In their mutation, they can carry the new
variants that generally have the potential to be more transmissible and, therefore, can attenuate
the immunity induced by the immunizers. The objective of this work was to theoretically find
the main inhibitors of S glycoprotein of SARS-CoV-2, using the methodology of drug design
De Novo, in the search for new antiviral agents, with the help of the MolAiCal computational
package, which used machine learning and artificial intelligence.
Descripción:
DJATA, Faustino. Estudo do Docking e da Dinâmica Molecular dos principais Inibidores da Glicoproteína
Spike do Sars-Cov-2 através de inteligência artificial. 2023, 22f. TCC - Curso de Química, Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Redenção-Ceará, 2023.
