In silico prediction of B-cell and T-cell epitopes of the Sudan Ebola virus glycoprotein for peptide-based vaccine design

Background Ebola virus disease (EVD) remains a deadly global health threat, especially due to the lack of approved vaccines or specific antiviral treatments specifically for Sudan ebolavirus (SUDV). The high mortality rate and recurring outbreaks of SUDV in sub-Saharan Africa call for urgent strategies to develop more effective and broadly protective vaccines for Ebola viruses. Methods This study used in silico immunoinformatics approaches to identify B-cell and T-cell epitopes from the Sudan ebolavirus glycoprotein for the development of a peptide-based subunit vaccine. Conserved sequences and antigenic motifs were predicted using MEME and IEDB tools in order to identify B-cell epitopes. T-cell epitopes were selected based on their immunogenicity, population coverage, and allergenicity using NetCTL 1.2, IEDB population coverage tools, and AllerCatPro 2.0, respectively. Molecular docking simulations were performed for the T-cell epitopes using HPEPDOCK 2.0, with validation through LigPlot + v2.2 and X-Score. Results This analysis led to the identification of two highly conserved B-cell epitopes that can be further tested in vitro—“IDQLVCKDHLASTDQLKSVGLNLEGSGVSTDIPSATKRWGFRSGVPPKVV” and “YEAGEWAENCYNLEIKKPDGSECLPPPPDGVRGFPRCRYVHKAQGTGPCP.” These also showed strong immunogenic potential from the analysis. Four T-cell epitopes—“YTENTSSYY,” “KCNPNLHYW,” “RLASTVIYR,” and “EVTEIDQLV”—showed strong immunogenic potential and high binding affinity (binding energy > 9.0 kcal/mol) to their respective HLA molecules. These T-cell epitopes also demonstrated extensive population coverage across different African regions. Conclusion The predicted B-cell and T-cell epitope sequences show strong potential for the development of peptide-based subunit vaccines against Sudan ebolavirus. Therefore, these findings may contribute to global vaccine development efforts of SUDV.