Prediction of Epitope-Based Peptides for Vaccine Development from Coat Proteins GP2 and VP24 of Ebola Virus Using Immunoinformatics

Abstract

This study aims to design epitope-based peptides for the utility of vaccine development by targeting Glycoprotein 2 (GP2) and Viral Protein 24 (VP24) of the Ebola virus (EBOV) that, respectively, facilitate attachment and fusion of EBOV with host cells. Using various databases and tools, immune parameters of conserved sequences from GP2 and VP24 proteins of different strains of EBOV were tested to predict probable epitopes. Binding analyses of the peptides with major histocompatibility complex (MHC) class I and class II molecules, population coverage, and linear B cell epitope prediction were peroformed. Predicted peptides interacted with multiple MHC alleles and illustrated maximal population coverage for both GP2 and VP24 proteins, respectively. The predicted class-I nonamers, FLYDRLAST, LFLRATTEL and NYNGLLSSI were found to cover the maximum number of MHC I alleles and showed interactions with binding energies of −7.8, −8.5 and −7.7 kcal/mol respectively. Highest scoring class II MHC binding peptides were EGAFFLYDRLASTVI and SPLWALRVILAAGIQ with binding energies of −6.2 and -5.6 kcal/mol. Putative B cell epitopes were also found on 4 conserved regions in GP2 and two conserved regions in VP24. Our in silico analysis suggests that the predicted epitopes could be a better choice as universal vaccine component against EBOV irrespective of different strains and should be subjected to in vitro and in vivo analyses for further research and development.