Immunoinformatical approach of Epitope based vaccine design for Dengu fever virus

Dengue virus (DENV) outbreaks are a major public health concern in India, necessitating the development of effective vaccination strategies. Existing dengue vaccines have limitations, such as incomplete protection against all virus serotypes and the risk of enhanced infection upon secondary exposure, driving the exploration of innovative vaccine development approaches. This study employs a combined reverse vaccinology and immunoinformatics approach to design a multi-epitope-based vaccine targeting various proteins of DENV. Computational immune-informatics techniques were utilized to identify B-cell and T-cell epitopes across the DENV genome, aiming to enhance the immune response against DENV infection. Bioinformatics tools were employed to predict epitopes, assess antigenicity, and conduct molecular docking to human HLA alleles. Peptides with the lowest binding affinity for each human allele were selected, and their structures were validated. The study identified promising vaccine candidates, including peptides from the whole genomes of DENV serotypes 1 (IGIGVLLTW), 2 (AAFSGVSWTM), 3 (WDFGSV), and 4 (NLEYTVVVTW). These findings highlight the potential of computational approaches in vaccine design, offering insights into novel strategies for combating DENV and potentially other infectious diseases.