Desenvolvimento de plataforma para produção de vacina baseada em BCG recombinante (rBCG) para a prevenção de infecções por SARS-CoV-2

• Autor(a) principal: Vara, Pedro Henrique Negreiros
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da PUC_RS
• Texto Completo: https://tede2.pucrs.br/tede2/handle/tede/10538
• topic: Vacina; SARS-CoV-2; COVID-19; rBCG; Multiepitópica; DNA; Vaccine; Subunit; Multi-epitope; COVID-19; SARS-CoV-2; rBCG; CIENCIAS BIOLOGICAS::BIOLOGIA GERAL

The continuous improvement in the vaccine development process is an extremely important step to mitigate the effects of the COVID-19 disease, an infection caused by SARS-CoV-2 and its variants, over varied regions in the world. A recombinant Mycobacterium bovis BCG (rBCG) is promising for a heterologous prime-boost vaccine protocol for virus infections. Consequently, the combination of immunoinformatic and deep neural network strategies make it possible to evaluate potential vaccine candidates with a cost-effective and convenient method, since in silico predictions can reduce the number of experiments needed for its validation. In this study, we identified the most conserved regions for 10 different SARS-CoV-2 proteins and by using an in silico deep learning approach identified antigenic vaccine subunits containing linear B-cell epitopes, cytotoxic T lymphocyte epitopes (CTL) and helper T lymphocyte epitopes (HTL) and developed a plasmid for a live bacterial vector for a recombinant vaccine. The final candidate was constructed with 12 vaccine subunits spliced together by AAY and GPGPG linkers, with 13 linear B-cell epitopes, 10 conformational B-cell epitopes, 76 CTL epitopes and 39 HTL epitopes. The population coverage for the combined CTL and HTL epitopes was estimated to be 98.49%. In silico tests were performed to validate the vaccine quality, showing that the multi-epitope recombinant protein is antigenic, non-allergenic and with adequate physicochemical properties. The secondary and tertiary (3D) structure of the final vaccine was also predicted, and its interaction with immune receptors (TLR3 and TLR4) evaluated by molecular docking. Additionally, results for the immune simulation indicate that the vaccine may elicit strong cellular and humoral immunity against the virus. Finally, codon optimization was performed to improve gene expression and, as a consequence, improve production of the recombinant vaccine. The rCPBMFMEV vaccine requires experimental and clinical validation but shows promising indicators that it can fight the SARS-CoV-2 viral infection.