Abstract

With the enormous genetic plasticity of malaria parasite, the challenges of developing a potential malaria vaccine candidate with highest efficacy still remain. This study has incorporated a bioinformatics-based screening approach to explore potential vaccine candidates in Plasmodium falciparum proteome. A systematic strategy was defined to screen proteins from the Malaria Parasite Metabolic Pathways (MPMP) database, on the basis of surface exposure, non-homology with host proteome, orthology with related Plasmodium species, and MHC class I and II binding promiscuity. The approach reported PF3D7_1428200, a putative metabolite transporter protein, as a novel vaccine candidate. RaptorX server was used to generate the 3D model of the protein and was validated by PROCHECK. Furthermore, the predicted B cell and T cell epitopes with the highest score were subjected to energy minimization by molecular dynamics simulation to examine their stability within a solvent system. Results from this study could facilitate selection of proteins for entry into vaccine production pipeline in future.

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