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Computational Prediction of Trypanosoma cruzi Epitopes Toward the Generation of an Epitope-Based Vaccine Against Chagas Disease
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Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is considered a Neglected Tropical Disease. Limited investment is assigned to its study and control, even though it is one of the most prevalent parasitic infections worldwide. An innovative vaccination strategy involving an epitope-based vaccine that displays multiple immune determinants originating from different antigens could counteract the high biological complexity of the parasite and lead to a wide and protective immune response. In this chapter, we describe a computational reverse vaccinology pipeline applied to identify the most promising peptide sequences from T. cruzi proteins, prioritizing evolutionary conserved sequences, to finally select a list of T and B cell epitope candidates to be further tested in an experimental setting. © 2023, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
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ROS LUCAS, Albert, et al. Computational Prediction of Trypanosoma cruzi Epitopes Toward the Generation of an Epitope-Based Vaccine Against Chagas Disease. Methods In Molecular Biology. 2023. Vol. 2673, num. 487-504. ISSN 1064-3745. [consulted: 5 of October of 2026]. Available at: https://hdl.handle.net/2445/205324