Daniela de Melo Resende, Alexandre B Reis and Jeronimo C Ruiz
Scientific Tracks Abstracts: J Vaccines Vaccin
Immunoinformatics is an innovative strategy for selection of targets for vaccine and diagnostics with reduced time and costs.
Data mining of essential sequences for eliciting protective immune responses through immunoinformatics has been used for
indicating good vaccine candidatesfor Neisseria meningitides and Staphylococcus aureus showing the efficacy of this approach.
It was also shown that instrinsically disorded proteins play important role in trypanosomatids virulence. Our hypothesis is that
protein disordered regions could be related to immunogenic epitopes facilitating their exposure to the immune system. In this
work, we developed a computational approach that integrates: a) T and B cell epitope predictors, namely: NetCTL and NetMHC
for T CD8+ epitope prediction; NetMHCII for T CD4+ epitope prediction; and BepiPred for B cell epitope prediction; and b)
structural disorder predictors, namely: DisEMBL, IUPred, GlobPipe and VSL2B. In addition, data associated with subcellular
location predictions performed by the algorithms WoLF PSORT (eukaryotic genomes), PSORTb (procariotic genomes),
Sigcleave (signal peptides) and TMHMM (transmembrane domains) were integrated in a relational database. The workflow
had been used for searching vaccine or diagnostic targets in prokaryotic and eukaryotic organisms, including Leishmania
infantum, Leishmania braziliensis, Schistosoma mansoni and Ehrlichia canis. Experiments in wet lab are being performed in
order to confirm the immunogenicity of the selected proteins from Leishmania and S. mansoni. The correlation between
structural disorder and the epitope location will be presented together with the analytical approach developed.