Epitope Mapping
and Vaccine Candidate Prediction for Listeriosis and Tetanus
Naravula Jalaja, Mundlamuri Ramesh and Yarramane Ajay
Res. J. Chem. Environ.; Vol. 29(3); 69-83;
doi: https://doi.org/10.25303/293rjce069083; (2025)
Abstract
In the pursuit to combat infectious diseases, the development of vaccines remains
a cornerstone of public health strategy. This study presents a novel in silico approach
to the design of multi-epitope vaccines against Listeria monocytogenes and Clostridium
tetani, pathogens responsible for significant morbidity and mortality worldwide.
Utilising advanced computational tools, we identified and characterised antigenic
and non-allergenic epitopes from surface proteins of these bacteria, essential for
eliciting a targeted immune response. Our analysis included the prediction of linear
B-cell epitopes using the ABCPred server, assessment of antigenicity with VaxiJen
and determination of epitope orientation within the cellular membrane via DeepTMHMM.
Molecular dynamics simulations provided insights into the stability and interactions
of the protein-peptide complexes, with RMSD and RMSF analyses confirming the structural
integrity conducive to vaccine efficacy. The strategic linking of shortlisted epitopes,
facilitated by the KK linker, led to the construction of vaccine candidates with
broad protective capabilities.
Our findings demonstrate the potential of computational methods in streamlining
vaccine development, offering a blueprint for rapid and efficient generation of
vaccine candidates against complex pathogens. The implications of this research
are far-reaching, providing a method that is both scientifically robust and technically
sound, capable of addressing the urgent need for new vaccines in the face of emerging
infectious diseases.
