Marburgvirus (MARV), a member of the Filovirus family, causes severe hemorrhagic fever in humans. Currently, there are no approved vaccines or post exposure treatment methods available against MARV. With the aim of identifying vaccine candidates against MARV, we employ different sequence-based computational methods to predict the MHC-I and MHC-II T-cell epitopes as well as B-cell epitopes for the complete MARV genome. We analyzed the variations in the predicted epitopes among four MARV variants, the Lake Victoria, Angola, Musoke, and Ravn. We used a consensus approach to identify several epitopes, including novel epitopes, and narrowed down the selection based on different parameters such as antigenicity and IC50 values. The selected epitopes can be used in various vaccine constructs that give effective antibody responses. The MHC-I epitope-allele complexes for GP and NP with favorably low IC50 values were investigated using molecular dynamics computations to determine the molecular details of the epitope-allele complexes. This study provides information for further experimental validation of the potential epitopes and the design and development of MARV vaccines.
Keywords: Bioinformatics; Epitopes; In silico prediction; Marburg virus; Molecular dynamics; Vaccine design.
Copyright © 2022 Elsevier B.V. All rights reserved.