Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/205324
Title: | Computational Prediction of Trypanosoma cruzi Epitopes Toward the Generation of an Epitope-Based Vaccine Against Chagas Disease |
Author: | Ros Lucas, Albert Rioja Soto, David Gascon, Joaquim Alonso Padilla, Julio |
Keywords: | Malaltia de Chagas Vacunes Chagas' disease Vaccines |
Issue Date: | 1-Jun-2023 |
Publisher: | Springer Nature |
Abstract: | 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. |
Note: | https://doi.org/10.1007/978-1-0716-3239-0_32 |
It is part of: | Methods In Molecular Biology, 2023, vol. 2673, p. 487-504 |
URI: | http://hdl.handle.net/2445/205324 |
Related resource: | https://doi.org/10.1007/978-1-0716-3239-0_32 |
ISSN: | 1064-3745 |
Appears in Collections: | Llibres / Capítols de llibre (ISGlobal) |
Files in This Item:
File | Description | Size | Format | |
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3. MIMB_Tcruzi_epitopes.docx.pdf | 278.42 kB | Adobe PDF | View/Open Request a copy |
Document embargat fins el 1-6-2025
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