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The integration of Reverse Vaccinology (RV) with structure-based protein design has been proposed as an optimal approach for the discovery and development of next-generation vaccines. In this project, we aim to develop a multi- and inter-disciplinary SV approach that integrates structural and computational biology with immunological tests and industrial protein production to: 1) identify epitopes from selected antigen candidates; 2) optimize epitope properties via rational design, for the development of vaccines; 3) produce antibodies that selectively recognize the identified antigens; 4) select antibodies to be used as diagnostic tools. This approach will focus on antigens from the Gram-negative pathogens Burkholderia pseudomallei, the etiological agent of melioidosis, and Burkholderia cenocepacia, an opportunistic pathogen affecting Cystic Fibrosis patients.
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