Construção in silico de uma vacina multi-epítopo contra o gênero Rickettsia através de imunoinformática

Abstract

The genus Rickettsia, belonging to the phylum Proteobacteria, is mainly composed of four groups of microorganisms: the typhus group, the spotted fever group, the ancestral group and the transitional group. These species cause diseases of public health importance, for example epidemic typhus, murine typhus, Rocky Mountain spotted fever, and Mediterranean spotted fever. Despite the increasing number of cases, there is still no vaccine against the diseases caused by this genus. This work aims at the in silico development of a multi-epitope vaccine with immune potential against the genus Rickettsia. Then eight proteins previously identified as potential vaccine candidates against these bacteria, went through a process of prediction of epitopes binding to histocompatibility complex molecules, type I and II, and then by quality analysis as to their antigenicity, allergenicity, toxicity. Those that passed this screening were joined with linkers and an adjuvant to form a chimeric multi-epitope protein, which underwent three-dimensional structure prediction and subsequent molecular docking analysis against the Toll Like-4 receptor present on host cells. Finally, the protein was tested for an immune response simulation using machine learning. A total of twenty-six immunogenic epitopes with 13 ligands for each type of histocompatibility complex molecule, were linked to construct the multi-epitope protein. The protein showed excellent immunogenic parameters and was not considered toxic or allergic to the host. In addition, it showed good stimulation of immune cells, with potential generation of memory cells. The in silico validations suggest a vaccine with efficacy against the action of these bacteria and must be validated in vitro.