Computational design of inhibitory peptides and an mRNA-Based multi-epitope vaccine targeting the MIC3 protein of Eimeriatenella.

This study addresses coccidiosis, a prevalent disease causing significant economic losses, and focuses on the EtMIC3 protein due to its critical role in Eimeria tenella pathogenesis. Our goal is to develop innovative therapeutic and preventive strategies leveraging the potential of the EtMIC3 protein. In this investigation, we evaluate the interaction of the EtMIC3 protein with its receptors, develop inhibitory peptides, and select epitopes from EtMIC3 using immunoinformatic tools. We assess the presentation of these epitopes to immune cells, model a multi-epitope protein, predict the mRNA structure, and evaluate the immune response to the newly designed vaccine. Docking studies indicated that the predicted peptides exhibited a strong affinity for binding to the EtMIC3 protein, with identified epitopes residing within the antigen-binding groove of their respective MHC alleles. The developed vaccine demonstrated stability, non-toxicity, and non-allergenicity, effectively eliciting responses from both the innate and adaptive immune systems. These findings suggest that the EtMIC3 protein is a promising target for both the inhibition of E. tenella and vaccine development. However, further validation through experimental and clinical studies is essential to corroborate these computational predictions.