Chagas Disease

2022 SAP Chagas Antigen Epitope Atlas

Screening and Identification of Metacaspase Inhibitors: Evaluation of Inhibition Mechanism and Trypanocidal Activity

A common strategy to identify new antiparasitic agents is the targeting of proteases, due to their essential contributions to parasite growth and development. Metacaspases (MCAs) are cysteine proteases present in fungi, protozoa, and plants. These …

The serological antibody repertoire in Chagas Disease

Towards a comprehensive description of the specificities of individual antibody repertoires in Chagas Disease

Target-based screening of the Chagas box: setting up enzymatic assays to discover specific inhibitors across bioactive compounds.

Chagas disease is a neglected tropical illness caused by the protozoan parasite Trypanosoma cruzi. The disease is endemic in Latin America with about 6 million people infected and many more being at risk. Only two drugs are available for treatment, …

Discovery and fine epitope mapping of novel serology-based markers for diagnosis of Congenital Chagas Disease using high-density peptide chips

How we use this technology to discover new antigens and epitopes in matched mother-newborn samples

Next-generation ELISA diagnostic assay for Chagas Disease based on the combination of short peptidic epitopes

Chagas disease, caused by the parasite Trypanosoma cruzi, is a life-long and debilitating illness of major significance throughout Latin America, and an emergent threat to global public health. Diagnostic tests are key tools to support disease …

Chagas Disease Diagnostic Applications: Present Knowledge and Future Steps

Immunomics of Infectious Diseases

High-throuput screening and data integration for diagnostics tool development

Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants

Setting the stage for high-throughput immunomics in Chagas Disease

Diagnostic peptide discovery: prioritization of pathogen diagnostic markers using multiple features