Computational Design Yields Self-Amplifying RNA Vaccine Candidates Against Marburg Virus

Marburg virus, a single-stranded RNA virus in the Orthomarburgvirus genus of the Filoviridae family, causes Marburg virus disease, a zoonotic illness with high morbidity and fatality rates, particularly in Africa. Despite its epidemic potential and its placement on the World Health Organization’s list of blueprint priority pathogens, no approved vaccines or efficient antiviral therapies currently exist for the virus. A new computational study has addressed this gap by applying immunoinformatics and reverse vaccinology to design two multi-epitope self-amplifying RNA vaccine candidates, named MB-saVaxI and MB-saVaxII.

The researchers targeted four viral proteins: the glycoprotein (GP), nucleoprotein (NP), VP40, and VP35. From the sequences of these proteins, they derived epitopes recognized by CD8+ T cells, CD4+ T cells, and B cells. Each candidate epitope was validated for antigenicity, non-allergenicity, non-toxicity, and conservation before being incorporated into the final vaccine constructs, a filtering step intended to retain only sequences likely to be both immunologically relevant and safe.

To enhance immunogenicity and stability, the selected epitopes were conjugated to suitable adjuvants through various linkers, allowing the design of a potentially stable vaccine molecule. The two constructs were then inserted into a standard self-amplifying RNA model in which the second open reading frame, ORF-2, encodes the target vaccine peptide, a configuration that enables the vaccine sequence to be amplified within host cells.

Biophysical analyses of the designed vaccines indicated favorable protein properties. Both MB-saVaxI and MB-saVaxII were predicted to be basic, with isoelectric points below 7; soluble, with grand average of hydropathicity values below 0; and stable, with aliphatic indices below 80. These metrics suggest the constructs are chemically plausible as vaccine antigens, although such predictions remain computational estimates rather than experimental measurements.

Molecular docking explored how the vaccine constructs might engage innate immune receptors. MB-saVaxI showed significant binding affinity to TLR2, with a docking score of −938.3, and to TLR4, at −902.4. MB-saVaxII docked to TLR3 at −1485.4 and to TLR7 at −1543.6. The detailed hydrogen-bond interactions underlying these complexes were validated by MM-GBSA calculations and molecular dynamics simulations, which tested whether the predicted binding poses remained stable over simulated time.

The study also examined manufacturability through in-silico cloning, in which both vaccine sequences were effectively inserted into Escherichia coli, a standard step for plasmid propagation in vaccine production workflows. The mRNA structures of MB-saVaxI and MB-saVaxII remained stable throughout the predicted expression pathway in the host, indicating that the designed transcripts are unlikely to adopt conformations that would disrupt translation in a real expression system.

Immune simulations provided a picture of how the candidates might perform immunologically. Both vaccines triggered robust innate and adaptive immunity in the simulations, with a sustained memory response and TH cell activation. This activation was evidenced by predicted production of interferon-gamma and interleukin-2, cytokines associated with effective TH1-type cellular immunity. The simulations also indicated that the vaccines elicited responses across the CD8+, CD4+, and B cell compartments built into their epitope design.

The authors emphasize that these findings are entirely computational. Extensive in-vitro and in-vivo studies are needed to conclusively establish the safety and efficacy of MB-saVaxI and MB-saVaxII. Docking scores, immune simulations, and biophysical predictions can prioritize candidates for laboratory testing, but they cannot substitute for experimental evidence. Nevertheless, by integrating epitope prediction, structural modeling, receptor docking, dynamics validation, and immune simulation into a single reverse vaccinology pipeline, the study offers a concrete, testable starting point for vaccine development against a pathogen for which no licensed countermeasure yet exists.

Subject of Research: Vaccinology

Article Title: Immunoinformatics and reverse vaccinology design of self-amplifying RNA vaccine against marburg virus with structural dynamics and immune simulation analysis

Article References: Rahman, M. A., Kabir, L., Ahmed, N., Barua, A., Hasan, M., & Mahdeen, A. A. (2026). Immunoinformatics and reverse vaccinology design of self-amplifying RNA vaccine against marburg virus with structural dynamics and immune simulation analysis. PLOS One, 21(10), e0361136. https://doi.org/10.1371/journal.pone.0361136

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0361136

Keywords: Marburg virus, self-amplifying RNA, reverse vaccinology, immunoinformatics, vaccine design, epitope prediction, molecular docking, immune simulation, Filoviridae, priority pathogens, reverse, vaccinology