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Open AccessJournal ArticleDOI

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

TLDR
A set of 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 are prioritized by means of a computer-aided strategy.
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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Journal ArticleDOI

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach.

TL;DR: The design of a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2 was found to be antigenic, almost neutral at physiological pH, non-toxic,non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage.
Journal ArticleDOI

The combination of artificial intelligence and systems biology for intelligent vaccine design.

TL;DR: This review explores the basics of artificial intelligence and systems biology approaches in the vaccine development pipeline and discusses epitope prediction tools for designing epitope-based vaccines and agent-based models for immune system response prediction, along with a focus on their potentiality to facilitate clinical trial phases.
Journal ArticleDOI

A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS-COV-2 by Comprehensive Immunoinformatic and Molecular Modelling Approach.

TL;DR: A comprehensive in silico strategy was used to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers and revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response.
Journal ArticleDOI

In silico design of an epitope-based vaccine against choline binding protein A of Streptococcus pneumoniae

TL;DR: It is proposed that MEV of CbpA could be a novel vaccine candidate, which may induce both humoral and cellular immune responses to non-serotype-specific pneumococcus, which is responsible for great morbidity and mortality globally.
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