mRNA vaccine design using the proteome of Theileria annulata through immunoinformatics approaches

ABSTRACT Theileriosis exerts a substantial impact on ruminants, resulting in significant economic losses within the animal husbandry sector. The current vaccine, a live attenuated parasite, has several limitations that hinder effective disease control. This study utilized immunoinformatics to prioritize potential vaccine candidates and pointed to the design of a novel mRNA vaccine against Theileria annulata using in silico methods. Nine antigenic proteins were selected using various software, and their epitopes were identified through immunoinformatics tools. These epitopes were assessed for their biological traits and homology. Their presentation by major histocompatibility complex (MHC) cells and other immune cells was analyzed using molecular docking techniques. A multi-epitope protein was then modeled and optimized, followed by structural and stability analyses of the mRNA vaccine construct. Finally, the immune response to the new vaccine was simulated. The identified epitopes were localized within the antigen-binding sites of their respective MHC alleles. The newly formulated vaccine demonstrated stability, exhibited no toxicity, and showed non-allergenic characteristics. It effectively elicited responses from both the humoral and cellular immune systems. The findings suggest that the desired engineered mRNA vaccine paves the way for the development of the deterrence of theileriosis. This potential merits additional exploration through rigorous laboratory experiments and subsequent clinical trials. IMPORTANCE This study presents a cutting-edge approach in vaccine design against bovine theileriosis, a devastating disease affecting cattle globally. By leveraging immunoinformatics methodologies, a novel mRNA vaccine candidate was tailored using computational analyzes of Theileria annulata proteins. Antigenic protein identification, epitope evaluation, and structural optimization of the multi-epitope mRNA vaccine are pivotal advancements in vaccine development. Using computational modeling tools to predict immune responses enhances the efficiency and accuracy of vaccine design, potentially revolutionizing preventive strategies against bovine theileriosis. This research not only demonstrates the potential of immunoinformatics in vaccine innovation but also sheds light on a promising avenue for combating a significant livestock health concern, offering hope for more effective and targeted veterinary interventions.