Immunoinformatics-Based strategies for mRNA vaccine development against ilesha virus

Ilesha virus is an arthropod-borne virus belonging to the genus Orthobunyavirus within the family Bunyaviridae. It has been isolated from humans in several African countries, primarily associated with febrile illness and erythema, although more severe manifestations such as fatal meningoencephalitis and hemorrhagic fever have also been reported. In this study, we employed immunoinformatics approaches to design a rational mRNA vaccine construct targeting the Ilesha virus, with the aim of preventing infection. Antigenic viral proteins were retrieved and analyzed using various bioinformatics tools to predict cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B-cell epitopes. These predicted epitopes were further evaluated for antigenicity, allergenicity, toxicity, and population coverage. The most immunologically promising epitopes were selected to construct two multi-epitope mRNA vaccine candidates. Each construct comprised nine epitopes, an adjuvant, an MHC class I-targeting domain (MITD), a Kozak sequence, 5′ and 3′ untranslated regions (UTRs), and appropriate linkers to ensure efficient expression and immune recognition. Both mRNA vaccine constructs were predicted to be highly antigenic, non-toxic, and non-allergenic, with favorable physicochemical properties and molecular weights of 118,528.86 Da (Construct 1) and 118,084.27 Da (Construct 2). Structural modeling revealed the constructs to be stable at both secondary and tertiary levels. Molecular docking with Toll-like receptors (TLRs) demonstrated strong binding affinities, with docking scores of –1149.5 and –882.6 for Construct 1 and Construct 2, respectively. This study presents a promising immunoinformatic strategy for developing an mRNA vaccine against Ilesha virus. The vaccine constructs show potential for eliciting protective immune responses; however, further in vitro and in vivo validation is necessary to confirm their efficacy and safety.

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Publication Details

Journal
In Silico Research in Biomedicine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.insi.2025.100046
Citations
2
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
1.61
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article

Immunoinformatics-Based strategies for mRNA vaccine development against ilesha virus

Glory Jesudara Oluwasanya, Elijah Kolawole Oladipo, Olatunji Matthew Kolawole, Esther Moradeyo Jimah et al.
2 citations
In Silico Research in Biomedicine
vaccines and immunoinformatics approaches
1.61
article

Immunoinformatics-Based strategies for mRNA vaccine development against ilesha virus

Glory Jesudara Oluwasanya, Elijah Kolawole Oladipo, Olatunji Matthew Kolawole, Esther Moradeyo Jimah, Tajudeen Oladunni Ganiyu, Titilayo Mabel Olotu, Bamidele Iwalokun, Helen N. Onyeaka, Elukunbi Hilda Awoyelu, James Akinwumi Ogunniran, Oluwaseyi Samuel Akinpelu
article en
2 citations

Abstract

Ilesha virus is an arthropod-borne virus belonging to the genus Orthobunyavirus within the family Bunyaviridae. It has been isolated from humans in several African countries, primarily associated with febrile illness and erythema, although more severe manifestations such as fatal meningoencephalitis and hemorrhagic fever have also been reported. In this study, we employed immunoinformatics approaches to design a rational mRNA vaccine construct targeting the Ilesha virus, with the aim of preventing infection. Antigenic viral proteins were retrieved and analyzed using various bioinformatics tools to predict cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B-cell epitopes. These predicted epitopes were further evaluated for antigenicity, allergenicity, toxicity, and population coverage. The most immunologically promising epitopes were selected to construct two multi-epitope mRNA vaccine candidates. Each construct comprised nine epitopes, an adjuvant, an MHC class I-targeting domain (MITD), a Kozak sequence, 5′ and 3′ untranslated regions (UTRs), and appropriate linkers to ensure efficient expression and immune recognition. Both mRNA vaccine constructs were predicted to be highly antigenic, non-toxic, and non-allergenic, with favorable physicochemical properties and molecular weights of 118,528.86 Da (Construct 1) and 118,084.27 Da (Construct 2). Structural modeling revealed the constructs to be stable at both secondary and tertiary levels. Molecular docking with Toll-like receptors (TLRs) demonstrated strong binding affinities, with docking scores of –1149.5 and –882.6 for Construct 1 and Construct 2, respectively. This study presents a promising immunoinformatic strategy for developing an mRNA vaccine against Ilesha virus. The vaccine constructs show potential for eliciting protective immune responses; however, further in vitro and in vivo validation is necessary to confirm their efficacy and safety.

In Silico Research in BiomedicineVol. 1
Fountain University (NG), University of Ilorin (NG), Kent State University (US), Adeleke University (NG), University of Warwick (GB), Ladoke Akintola University of Technology (NG), Nigerian Institute of Medical Research (NG), University of Birmingham (GB)
Openalex Percentile: Top 15%
vaccines and immunoinformatics approaches
1.61
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