In silico Design of an Epitope-Based Vaccine Ensemble for Chagas Disease

利用计算机模拟设计基于表位的恰加斯病疫苗组合

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Abstract

Trypanosoma cruzi infection causes Chagas disease, which affects 7 million people worldwide. Two drugs are available to treat it: benznidazole and nifurtimox. Although both are efficacious against the acute stage of the disease, this is usually asymptomatic and goes undiagnosed and untreated. Diagnosis is achieved at the chronic stage, when life-threatening heart and/or gut tissue disruptions occur in ~30% of those chronically infected. By then, the drugs' efficacy is reduced, but not their associated high toxicity. Given current deficiencies in diagnosis and treatment, a vaccine to prevent infection and/or the development of symptoms would be a breakthrough in the management of the disease. Current vaccine candidates are mostly based on the delivery of single antigens or a few different antigens. Nevertheless, due to the high biological complexity of the parasite, targeting as many antigens as possible would be desirable. In this regard, an epitope-based vaccine design could be a well-suited approach. With this aim, we have gone through publicly available databases to identify T. cruzi epitopes from several antigens. By means of a computer-aided strategy, we have prioritized a set of epitopes based on sequence conservation criteria, projected population coverage of Latin American population, and biological features of their antigens of origin. Fruit of this analysis, we provide a selection of CD8(+) T cell, CD4(+) T cell, and B cell epitopes that have <70% identity to human or human microbiome protein sequences and represent the basis toward the development of an epitope-based vaccine against T. cruzi.

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