Article: Multi-epitopes prediction for designing a candidate vaccine against Ebola virus: a reverse vaccinology and immunoinformatics approach Journal: International Journal of Data Mining and Bioinformatics (IJDMB) 2026 Vol.30 No.3/4 pp.265 - 290 Abstract: Over a span of four decades, the Ebola virus disease (EVD) outbreak, has wreaked havoc starting from Central African countries through to different parts of the world including Asian countries. Guinea was the first to witness the catastrophe followed by many African and Asian countries including Liberia and Sierra Leone. In this study, the immunoinformatics approach which would include both B cell and T cell epitopes has been used for candidate vaccine development against EVD. The prediction of B cell and T cell epitopes was done by targeting the glycoprotein (GP) and VP40 proteins of Ebolavirus and an antigenic multi-epitope vaccine construct was designed. The vaccine construct was then docked with human immunogenic Toll-like Receptor 4 (TLR 4) having binding energy - 13,883.1 and in silico immune simulation was done to predict the immunogenic potential of the vaccine construct with the CAI of 0.94 and the GC content 54.35 as it showed efficient expression in Escherichia coli (E. coli) K12 strain which produced vaccine in wide scale. The Ebola virus vaccine construct designed through the immunoinformatics approach in this study could be useful in combatting EVD. Inderscience Publishers - linking academia, business and industry through research

Title: Multi-epitopes prediction for designing a candidate vaccine against Ebola virus: a reverse vaccinology and immunoinformatics approach

Authors: Swati Mohanty; Himanshu Singh

Addresses: Department of Bioinformatics, School of Bioengineering and Biosciences, Lovely Professional University, Jalandhar, 144411, Punjab, India ' Department of Bioinformatics, School of Bioengineering and Biosciences, Lovely Professional University, Jalandhar, 144411, Punjab, India

Abstract: Over a span of four decades, the Ebola virus disease (EVD) outbreak, has wreaked havoc starting from Central African countries through to different parts of the world including Asian countries. Guinea was the first to witness the catastrophe followed by many African and Asian countries including Liberia and Sierra Leone. In this study, the immunoinformatics approach which would include both B cell and T cell epitopes has been used for candidate vaccine development against EVD. The prediction of B cell and T cell epitopes was done by targeting the glycoprotein (GP) and VP40 proteins of Ebolavirus and an antigenic multi-epitope vaccine construct was designed. The vaccine construct was then docked with human immunogenic Toll-like Receptor 4 (TLR 4) having binding energy - 13,883.1 and in silico immune simulation was done to predict the immunogenic potential of the vaccine construct with the CAI of 0.94 and the GC content 54.35 as it showed efficient expression in Escherichia coli (E. coli) K12 strain which produced vaccine in wide scale. The Ebola virus vaccine construct designed through the immunoinformatics approach in this study could be useful in combatting EVD.

Keywords: Ebola virus; epitope-based vaccine; molecular docking; immunoinformatics; reverse vaccinology.

DOI: 10.1504/IJDMB.2026.154694

International Journal of Data Mining and Bioinformatics, 2026 Vol.30 No.3/4, pp.265 - 290

Received: 22 Mar 2024
Accepted: 23 Oct 2024
Published online: 10 Jul 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Multi-epitopes prediction for designing a candidate vaccine against Ebola virus: a reverse vaccinology and immunoinformatics approach

Keep up-to-date