A Potential Malaria Vaccine Candidate Identified Using an Insilico Approach
The search for an effective malaria vaccine has yielded no success yet. Unfortunately, resistance to post-infection treatments is on the increase hence the need to develop an efficient vaccine. The aim of many reverse vaccinology studies is to identify novel proteins found exposed on the surface. Many malaria vaccine candidates can be effective tools against malaria but gross allelic polymorphism is a major hinderance which could be overcome by using highly conserved proteins. Also peptide based vaccines can be of great importance in fighting malaria however this is limited by HLA restriction which can be maneuvered by using promiscuous peptides. In the current work, our objective was to computationally identify conserved hypothetical, antigenic, surface proteins in pathogenic plasmodium falciparum parasite. So in this study, we employed an in silico approach to screen the proteins on the basis of surface localization, non-homology with host proteome, and MHC class I and II binding promiscuity. The analyses reported XP_001351004.1 an uncharacterized protein as a novel vaccine candidate. Generation of the 3D model of the protein was done using RaptorX server. Furthermore, the B cell and T cell epitopes were also predicted. B cell epitopes were predicted using ABCpred and Kolanskar and Tongaonkar antigenicity method while Tcell epitopes were predicted using CTLpred.
Five peptides were selected based on their hydrophobicity. Results from this study could be extended to in-vivo and in-vitro experiments for future vaccine development.
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