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ShinyVar: a web-based application for comparative Influenza variant analysis supporting structure-guided approaches to vaccine and antiviral drug design

bioinformatics
genetics
genomics
drugs-and-devices
infectious-diseases

Abstract

Background. Influenza viruses remain a significant global health threat due to their high mutation rates and extensive subtype diversity. Genetic variability promotes the mixing of viral subpopulations and facilitates the emergence of novel, potentially virulent strains. Seasonal influenza vaccines, typically targeting A/H1N1, A/H3N2, B/Victoria, and B/Yamagata subtypes, are reformulated annually, but vaccine design and antiviral resistance are affected by antigenic drift, such as the H275Y mutation, which confers highly reduced sensitivity to the influenza medication oseltamivir.

Methods. Here, we present ShinyVar, a web-based application developed using the R Shiny framework, for comparative variant analysis. The application supports the structural modeling of influenza virus subtypes for vaccine and antiviral drug design. Using next-generation sequencing data, ShinyVar enables users to visualize and compare genetic variations identified across multiple influenza virus subtypes over several years. Identified variants are interactively displayed, and hemagglutinin (HA) and neuraminidase (NA) protein sequences are used to generate 3D models via SWISS-MODEL. Structural comparisons and molecular docking were performed with HADDOCK and AutoDock Vina to evaluate the impact of mutations on antibody and antiviral binding.

Results. Variant analysis revealed 181 variants in B/Victoria (2025), 101 in A/H1N1 (2024), 37 in A/H3N2 (2024), and 7 in B/Yamagata (2025). Structural analysis focused on HA_A/H1N1, NA_A/H1N1, and NA_B/Victoria. In HA_A/H1N1, eight non-synonymous mutations were identified; notably, p.Thr137Ala led to the loss of a hydrogen bond within the 5J8 antibody binding site, resulting in a slight decrease in binding affinity. NA_A/H1N1 mutations caused minimal conformational change but slightly reduced oseltamivir binding affinity. NA_B/Victoria mutations marginally disrupted key oseltamivir interaction residues (E276, R292), resulting in lower binding affinity than NA_A/H1N1.

Conclusions. ShinyVar enables the intuitive analysis of next-generation sequencing data without coding expertise and supports downstream structural modeling and docking. It offers insights into influenza virus evolution and contributes to the design of more effective vaccines and antivirals.

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