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Multi-epitope vaccine candidate design for dengue virus 



A Dharani, DR Ezhilarasi, G Priyadarsini & PA Abhinand*



Department of Bioinformatics, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai 600 116, India;

*Corresponding author



PA Abhinand - E-mail: p.a.abhinand@sriramachandra.edu.in; Phone: +91 9884351442

A Dharani - E-mail: dharani.arunraj20@gmail.com

DR Ezhilarasi - E-mail: ezhilarasirajha@gmail.com

G Priyadarsini - E- mail: priyadarsini1608@gmail.com


Article Type

Research Article



Received May 1, 2023; Revised May 31, 2023; Accepted May 31, 2023, Published May 31, 2023



Dengue Fever (DF) is a vector-borne neglected viral disease with a high burden in the sub-tropics of Asia and Africa. Aedes aegypti is responsible for 90% of cases in the global burden of disease. The primary goal of the treatment is to eliminate the virus from the bloodstream of affected individuals. A successful dengue vaccine must elicit both neutralizing antibodies and cell-mediated immunity and there is no vaccine to date to prevent DF. A multi-epitope vaccine composed of a series of or overlapping peptides is, therefore, an ideal approach for the prevention and treatment of pathogenic organisms. An immunoinformatics approach was employed to design a theoretical multi-epitope vaccine candidate. This vaccine candidate consists of linear B-cell epitope, TH cells epitope and CTL of reported potential vaccine candidates. These epitopes were linked together with suitable linkers and adjuvant at the N terminal and C terminal. The 3D Structure of the vaccine was modeled, refined and validated using computational tools. Protein-protein docking of vaccine candidates with TLR3 protein results in efficient binding. Immune stimulation of vaccine candidates predicted high levels of IgG and IgM. This candidate vaccine should be validated experimentally using suitable in-vivo and in-vitro studies to use in dengue fever virus elimination programmes.



Dengue, linkers, epitope, antigen, antibody, docking, immune simulation



Dharani et al. Bioinformation 19(5): 628-632 (2023)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.