Computational Identification and Immunoinformatic Design of a Multiepitope Vaccine Candidate against Marburg Virus Disease Using Reverse Vaccinology
Vivaan Dhawan
United World College of South East Asia (UWCSEA), Singapore.
Vikas Jha *
National Facility for Biopharmaceuticals, G. N. Khalsa College, Matunga, Mumbai, Maharashtra, India.
*Author to whom correspondence should be addressed.
Abstract
Marburg virus disease (MVD) is a highly lethal hemorrhagic fever caused by Marburg virus, a priority pathogen with no approved vaccines or antiviral treatments. In this study, an integrated reverse vaccinology and immunoinformatics pipeline was employed to systematically screen the Marburg virus proteome and identify immunodominant B-cell, CD8⁺ T-cell, and CD4⁺ T-cell epitopes suitable for multiepitope vaccine design. Physicochemical and structural analyses revealed the viral glycoprotein and nucleoprotein as the most antigenically relevant proteins, with the glycoprotein exhibiting extensive surface-exposed and allele-promiscuous epitope clusters. High-affinity MHC class I and II epitopes, along with accessible B-cell epitopes, were further validated through molecular docking with representative HLA alleles and neutralizing antibodies. A 284-amino-acid multiepitope vaccine construct incorporating hBD-3 adjuvant, PADRE sequence, CTL epitopes, HTL epitopes, and B-cell epitopes was subsequently designed using optimized linker arrangements. Bioinformatic validation demonstrated that the construct is highly antigenic, non-allergenic, non-toxic, structurally stable, and predicted to elicit strong humoral and cellular immune responses. These findings provide a robust computational foundation for developing an effective vaccine against Marburg virus, warranting further experimental and preclinical evaluation.
Keywords: B-cell epitopes, filoviruses, glycoprotein, immunoinformatics, Marburg virus, multiepitope vaccine, reverse vaccinology, T-cell epitopes, vaccine design, viral proteome