Designing a multi-epitope vaccine against dengue virus-2 using in silico tools for expression in plant systems

Dengue virus (DENV), transmitted by Aedes mosquitoes, remains a serious global health threat with an increasing incidence, largely due to its complex epidemiology and the impact of climate change. DENV belongs to the Flaviviridae family, comprising four serotypes (DENV-1 to DENV-4). The high mutation rate of DENV and the risk of antibody-dependent enhancement (ADE) complicate the development of a vaccine. This study aims to design a multi-epitope vaccine against DENV, with a focus on DENV-2, the strain associated with severe symptoms.

First, the genome of DENV-2 was analyzed and vaccine candidate proteins were identified by examining properties such as immunogenicity, toxicity, and allergenicity. The secondary and tertiary structures of the vaccine were predicted and validated, and the vaccine interaction with MHC receptors was analyzed through docking. The stability and flexibility of the vaccine were also evaluated by molecular dynamics simulation. Finally, the vaccine gene sequence was optimized for expression in Nicotiana benthamiana and cloned into the pBI121 vector.

In this study, four proteins were selected from the initial 10 proteins after eliminating those that were allergens, toxins, or had homology to human or mouse proteins. Finally, protein 3 was identified as the source antigen for epitope prediction and vaccine construction. This highly immunogenic, non-toxic, and non-allergenic protein, located in the cytoplasm, was used to design a multi-epitope vaccine that includes selected epitopes, an IL-12 adjuvant, and a His tag. The designed vaccine consisted of 380 amino acids, exhibited a suitable stability index, and possessed a valid three-dimensional structure, with 95.4% of the amino acids located in the preferred region of the Ramachandran map. Docking and dynamic simulations demonstrated a stable interaction between the vaccine and MHC-I and MHC-II receptors. Also, the vaccine gene sequence was cloned into the pBI121 vector for optimal expression in N. benthamiana with a codon compatibility index of 0.78 and a GC content of 50.53%.

This study demonstrates the potential of computational approaches for developing targeted vaccines against dengue fever. Additionally, molecular farming offers a promising, safe, and cost-effective method for large-scale production of vaccines. Future research should focus on preclinical and clinical trials to validate the safety and efficacy of the vaccine.