# Designing a broad-spectrum multi-epitope vaccine against influenza A and Mycoplasma pneumoniae: an immunoinformatics approach

## TL;DR

This paper presents a new multi-epitope vaccine design targeting both influenza A and Mycoplasma pneumoniae using immunoinformatics methods.

## Contribution

A novel dual-target multi-epitope vaccine is designed using immunoinformatics to protect against two respiratory pathogens.

## Key findings

- The vaccine includes epitopes from influenza A and Mycoplasma pneumoniae proteins with high antigenicity and immunogenicity.
- The vaccine structure is stable, soluble, and has minimal allergy risk with strong immune receptor binding.
- The vaccine could cover 97.07% of the global population, including high efficacy in North America and East Asia.

## Abstract

Influenza A and Mycoplasma pneumoniae (M. pneumoniae) are common respiratory pathogens, causing severe co-infections in clinical diseases. Current vaccines have failed to provide comprehensive protection against both of the pathogens, highlighting the requirement of integrated solution.

In this study, a novel dual-target multi-epitope vaccine was developed based on the immunoinformatics method. Based on the consistent sequences, we used the HA and NA proteins of influenza A virus, and the p1, p65, HMW1-3 proteins of M. pneumoniae to determine the immunodominant T- and B-cell epitopes.

The designed vaccine included 21 linear B-cell epitopes, 34 CTL epitopes and 19 HTL epitopes from influenza A virus and M. pneumoniae. The selection was based on antigenicity, immunogenicity, and alignment with previously validated epitopes. Structural and physicochemical assessments indicated that the vaccine had high stability, solubility, and minimal allergy risk. Molecular docking with TLR3 and TLR4 receptors revealed strong binding, suggesting robust immune activation. Population coverage analysis showed the vaccine could cover 97.07% of the global population, with high efficacy across key regions such as North America and East Asia. In this study, we provided an immunoinformatics approach for vaccine design.