Development of designed site-directed pseudopeptide-peptido-mimetic immunogens as novel minimal subunit-vaccine candidates for malaria

Synthetic vaccines constitute the most promising tools for controlling and preventing infectious diseases. When synthetic immunogens are designed from the pathogen native sequences, these are normally poorly immunogenic and do not induce protection, as demonstrated in our research. After attempting many synthetic strategies for improving the immunogenicity properties of these sequences, the approach consisting of identifying high binding motifs present in those, and then performing specific changes on amino-acids belonging to such motifs, has proven to be a workable strategy. In addition, other strategies consisting of chemically introducing non-natural constraints to the backbone topology of the molecule and modifying the a-carbon asymmetry are becoming valuable tools to be considered in this pursuit. Non-natural structural constraints to the peptide backbone can be achieved by introducing peptide bond isosters such as reduced amides, partially retro or retro-inverso modifications or even including urea motifs. The second can be obtained by strategically replacing L-amino-acids with their enantiomeric forms for obtaining both structurally site-directed designed immunogens as potential vaccine candidates and their Ig structural molecular images, both having immunotherapeutic effects for preventing and controlling malaria.

Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models

Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria.