# Clinical Serum-Anchored Computational Design Pipeline for a Broad-Spectrum Influenza Multi-Epitope mRNA Vaccine

## TL;DR

This paper introduces a new pipeline for designing broad-spectrum influenza mRNA vaccines using real patient blood samples and computer modeling to identify effective immune targets.

## Contribution

The study introduces a clinical serum-anchored pipeline that combines real-world immune data with computational modeling to design broad-spectrum influenza vaccines.

## Key findings

- 12 immunodominant B-cell epitopes were identified from influenza A and B nucleoproteins using patient sera.
- MEMV vaccine candidates achieved 95.63% global HLA coverage and showed favorable immune compatibility in simulations.
- The pipeline enables faster vaccine design and provides a strategy for epitope combination with high antigenicity and safety.

## Abstract

Influenza remains a major global health threat because the virus mutates constantly, often making traditional vaccines less effective. To address this challenge, this study developed a new method for designing "broad-spectrum" mRNA vaccines that protect against multiple influenza virus strains. Unlike previous methods that relied entirely on computer predictions, this approach used real blood samples from vaccinated people and from patients with influenza to identify specific epitopes that trigger a strong and long-lasting immune response. By combining these real-world biological markers with advanced computer modeling, the researchers constructed three new vaccine candidates. Computer simulations confirmed that these vaccine candidates are safe, stable, and capable of covering approximately 95.63% of the global population. This “clinical serum-anchored” design pipeline bridges the gap between theoretical design and real-world application, offering a faster and more reliable way to develop effective vaccines for future flu outbreaks.

Influenza’s pandemic threat is driven by antigenic drift, which limits the efficacy of conventional vaccines. To address this challenge, we established a clinical serum-anchored computational design pipeline for a broad-spectrum multi-epitope mRNA vaccine (MEMV), bridging the gap between pure in silico design and clinical applicability. Using 36 longitudinal sera (d0/d28/d365) from 12 well-characterized human cohorts (6 vaccine recipients and 6 influenza patients) and high-density antibody-peptide microarrays, we empirically identified 12 immunodominant B-cell linear epitopes from the nucleoprotein (NP) of influenza A (H1N1/H3N2) and B viruses. These experimentally validated epitopes were combined with in silico-predicted conserved helper T-lymphocyte (HTL)/cytotoxic T-lymphocyte (CTL) epitopes (from NP/HA/NA) to construct MEMVs candidates, ensuring high antigenicity, non-toxicity, and 95.63% global HLA coverage. Molecular docking and 100 ns molecular dynamics (MD) simulations confirmed favorable conformational compatibility between MEMVs and Toll-like receptor 3 (TLR3) in silico immunization via C-ImmSim predicted robust B/T-cell responses and protective cytokine (IFN-γ/IL-10) production. Collectively, this pipeline shortens the preliminary design cycle for influenza vaccines, provides a standard epitope-combination strategy, and offers direct targets for follow-up in vitro/in vivo experiments.