Structure-guided epitope engineering enables precision plant virus immunodiagnostics

Plant viruses cause major agricultural losses, necessitating sensitive, scalable, and economically viable diagnostic tools. While monoclonal antibodies provide high specificity, their high production costs limit routine deployment, whereas conventional polyclonal antisera often exhibit nonspecific reactivity. Here, we report a structure-guided peptide immunodiagnostic strategy for developing low-cost polyclonal antibodies with improved diagnostic specificity against Capillovirus mali and Ilarvirus ApMV . Coat proteins were modeled using AlphaFold3 and evaluated for predicted accessibility, physicochemical properties, RNA-protein interaction regions to prioritize candidate epitope regions. The selected epitopes were experimentally evaluated through antibody generation and immunodiagnostic assays including peptide-competition ELISA. Analyses across filamentous and icosahedral viruses identified accessibility- and flexibility-associated features of successful epitopes, providing a framework for rational peptide immunodiagnostic design. Peptide-derived polyclonal antibodies demonstrated improved specificity and reduced background reactivity compared with conventional full-length coat protein antisera in ELISA. The findings were further evaluated using RT-PCR, dot immunobinding, and western blotting assays, while incorporation of epitope-specific polyclonal antibodies into lateral flow immunoassays, provided clearer test line signals and supported target-specific detection. Collectively, these findings suggest that predicted structural accessibility and physicochemical properties may contribute to immunodiagnostic performance and support a structure-guided framework for rational peptide selection in plant virus diagnostics.