Abstract
Cholera is an acute, highly contagious diarrheal disease caused by the gram-negative bacterium Vibrio cholerae, typically contracted through contaminated water or food. Without timely treatment, cholera can lead to severe dehydration and death. The COVID-19 pandemic has underscored the critical importance of vaccine development, emphasizing the need for effective vaccines against various diseases. Despite the complexity and high costs associated with vaccine design, advancements in bioinformatics and immunoinformatics offer computational methods that accelerate research and provide valuable immunological insights. In this study, we utilized computational approaches to design a multi-epitope vaccine against V. cholerae. We started with the V. cholerae genome and identified 19,155 possible antigens, all of which underwent various computational filters to determine the best candidates. Finally, we identified the two best antigens for vaccine development. One of the key achievement of our study was the identification of these antigens, as they successfully passed all computational tests among all possible antigens. This finding may open new immunological pathways in designing vaccines against V. cholerae. These antigens served as the foundation for identifying B-cell, MHC I, and MHC II epitopes. Using linkers and an adjuvant, these epitopes formed the core components of our vaccine. The designed vaccine underwent multiple evaluations and successfully passed all assessments, demonstrating its potential efficacy.