AstraMEV (AI-Guided Structural Assembly of Multi-Epitope Vaccines) Against Infectious Bronchitis Virus

Infectious bronchitis virus (IBV) continues to threaten the poultry industry due to its rapid mutation and genetic diversity. We introduce AstraMEV, a predictive structural immunoinformatic platform that leverages genomic screening of 56 IBV genomes to identify conserved epitopes from the nucleocapsid (N) and spike (S) proteins. Two multiepitope vaccine constructs, SmallTope and BigTope, were designed and refined using AI-driven methods such as RFdiffusion and ProteinMPNN to optimize structural stability and immunogenicity. Molecular dynamics simulations confirmed the constructs' stability and effective binding to chicken Toll-like receptor 4 (chTLR4). Crucially, Poisson-Boltzmann calculations revealed that certain computationally derived variant epitopes significantly improved the binding enthalpy, highlighting key interaction domains. Our comprehensive approach demonstrates the feasibility of leveraging computational immunoinformatics for targeted vaccine design. These findings underscore AstraMEV's robust potential for next-generation IBV vaccines and broader applications in combating rapidly evolving pathogens with significant global impact.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-10-23
DOI
https://doi.org/10.1021/acs.jcim.5c01809
Citations
1
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.81
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article

AstraMEV (AI-Guided Structural Assembly of Multi-Epitope Vaccines) Against Infectious Bronchitis Virus

Sakib Ferdous, Supantha Dey, Roya Salehi, Hilary Gates et al.
1 citations
Journal of Chemical Information and Modeling
vaccines and immunoinformatics approaches
0.81
article

AstraMEV (AI-Guided Structural Assembly of Multi-Epitope Vaccines) Against Infectious Bronchitis Virus

Sakib Ferdous, Supantha Dey, Roya Salehi, Hilary Gates, Riza Danurdoro
article en
1 citations

Abstract

Infectious bronchitis virus (IBV) continues to threaten the poultry industry due to its rapid mutation and genetic diversity. We introduce AstraMEV, a predictive structural immunoinformatic platform that leverages genomic screening of 56 IBV genomes to identify conserved epitopes from the nucleocapsid (N) and spike (S) proteins. Two multiepitope vaccine constructs, SmallTope and BigTope, were designed and refined using AI-driven methods such as RFdiffusion and ProteinMPNN to optimize structural stability and immunogenicity. Molecular dynamics simulations confirmed the constructs' stability and effective binding to chicken Toll-like receptor 4 (chTLR4). Crucially, Poisson-Boltzmann calculations revealed that certain computationally derived variant epitopes significantly improved the binding enthalpy, highlighting key interaction domains. Our comprehensive approach demonstrates the feasibility of leveraging computational immunoinformatics for targeted vaccine design. These findings underscore AstraMEV's robust potential for next-generation IBV vaccines and broader applications in combating rapidly evolving pathogens with significant global impact.

Journal of Chemical Information and ModelingVol. 65(21)
Iowa State University (US)
Openalex Percentile: Top 22%
vaccines and immunoinformatics approaches
0.81
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AstraMEV (AI-Guided Structural Assembly of Multi-Epitope Vaccines) Against Infectious Bronchitis Virus — Sakib Ferdous, Supantha Dey, et al. · Journal of Chemical Information and Modeling (2025) | TGRS Research Map | TGRS