Multi Epitope Peptide Vaccine Prediction against Sudan Ebola Virus Using Immuno-Informatics Approaches

Abstract

Sudan Ebola virus is single stranded negative sense RNA genome belonging to Filovirus Filoviridae family that causes hemorrhagic fever. There is no treatment or vaccine for it, thus the aim of this study is to design a peptide vaccine using immuoinformatics approaches to analyse the glycoprotein of the all strain of SUDV, to determine the conserved region which is further studied to predict all possible epitopes that can be used as a peptide vaccine. A total of 21 Sudan Ebola virus glycoprotein retrieved from NCBI database were aligned to determine the conservancy and to predict the epitopes using IEDB analysis resource. Three epitopes predicted as a peptide vaccine for B cell (PPPPDGVR, ETFLQSPP, LQSPPIRE). For T cell four epitopes showed high affinity to MHC class I (FLYDRLAST, IIIAIIALL, MHNQNALVC and RTYTILNRK) and high coverage against Sudan and the whole world population. Also in MHC class II, Four epitopes that interact with most frequent MHC class II alleles (FAEGVIAFL, FLRATTELR, FLYDRLAST and FVWVIILFQ) with high coverage against Sudan and the whole world population. We recommend in vivo and in vitro study to prove the effectiveness of these predicted epitopes as a peptide vaccine.