Raul Acosta Murillo


National Network of Youth Activities in Science and Technology in Mexico (laREDMex)

In silico design and production of a multiepitope peptide vaccine against dengue virus (DENV).

Dengvaxia®, the only approved vaccine for treating dengue fever, requires prior laboratory-confirmed infection, which poses a higher risk of severe disease for those without previous exposure. In this study, a simulation-based approach was used to design an effective multiepitope peptide vaccine against the dengue virus (DENV). This technology might reduce the risk of presenting antibody-enhanced disease as it generates protection against the conserved regions among the different dengue serotypes. During this study, different serotypes of dengue virus were analysed by detecting similarities among their membrane proteins, after that, epitopes, meaning specific regions that trigger an immune response, were carefully selected from those membranes based on their conservation and ability to activate an immune reaction. To ensure safety, we excluded epitopes that may pose risks such as allergenicity, toxin potential, or similarity to human proteins. An arrangement of the selected epitopes was created prioritizing their potential to provoke an immune response through specific linker proteins resulting in the new vaccine design. The protein’s 2D and 3D structures were obtained through modelling and refinement techniques. The effectiveness of the designed peptide vaccine was obtained by using immunoinformatics analysis. The vaccine sequence was optimized and adapted for production.