Computational analysis in designing T cell epitopes enriched peptides of Ebola glycoprotein exhibiting strong binding interaction with HLA molecules

Abstract

Computational approach has shown remarkable progress in epitope mapping, paving the way to finding vaccine candidates against different viruses. In the current study, prediction algorithms and molecular docking were applied to select peptides containing multiple Ebola glycoprotein epitopes showing interaction with different HLA molecules. Six peptides containing overlapping multiple HLA I (CD8+) and II (CD4+) restricted T cell epitopes were generated via consensus approach applying six different prediction tools. Four (P1, P2, P5 and P6) out of six peptides were selected after screening for absence of undesirable responses and presence of B cell epitopes. Peptide-HLA interaction analysis based on Autodock Vina and CABS-dock showed strong binding of these four peptides with eighteen HLA molecules. HLA coverage analysis from each prediction tool showed that these peptides were able to bind to diverse HLA-A, HLA-B, HLA-DP, HLA-DQ and HLA-DR alleles. Population coverage analysis of peptides for expected immune response in four different continents (Africa, America, Asia and Europe) have shown average population coverage viz, P1 (95%), P2 (96%), P5 (91%) and P6 (94%). Further, these peptides were found to be nearly 100% conserved in Zaire Ebola virus while LANETTQALQLF (P5) was found to be 100% conserved in Zaire, Sudan, Bundibugyo and Tai Forest species. Therefore, these peptides capable of inducing T and B cell response and being presented by a wide range of HLA molecules have a strong potential to be part of diagnostic and preventive tools against Ebola virus disease.