Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

Abstract

Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host–pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1–4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2 show that these candidate vaccines perfectly fit into the binding domains of the receptors. In addition, DV-1 has a better binding energies of − 60.07, − 63.40, − 69.89 kcal/mol against MHC-1, TLR-2, and TLR-4, with respect to the other vaccines. All the designed vaccines were highly antigenic, soluble, non-allergenic, non-toxic, flexible, and topologically assessable. The immune simulation analysis showed that DV-1 may elicit specific immune response against dengue virus. Moreover, codon optimization and in silico cloning validated the expressions of all the designed vaccines in E. coli. Finally, the molecular dynamic study shows that DV-1 is stable with minimum RMSF against TLR4. Immunoinformatics tools are now applied to screen genomes of interest for possible vaccine target. The designed vaccine candidates may be further experimentally investigated as potential vaccines capable of providing definitive preventive measure against dengue virus infection.

In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

“…The physicochemical properties of the retrieved proteins were predicted before antigenic determination of their sequences 96 . Using the threshold of 0.4, the viral components were classified into antigens and non-antigens (scores below the threshold) using the VaxiJen server.…”

“…To develop a good vaccine, it must be able to induce immunity through the antigen with a durable adaptive immunity and it should possess antigenic properties, which are important to elicit the immune response of the host 96 .…”

“…The host innate immune responses in vertebrates (retinoic acid-inducible gene I RIG-I) 17 , and Toll-like receptors (TLRs) 18 have been reported to play a substantial role in limiting CCHFV pathogenesis 22 , 23 . Also, the role of TLR2 and TLR4 in the recognition of viral structural proteins leading to inflammatory cytokine production has been reported 96 , 116 . To explore specific interactions and binding affinities of the final subunit multi-epitopes vaccine construct, against TLR2, TLR3, and TLR4 and major histocompatibility complexes MHC I and II, molecular docking were done.…”

Immunoinformatics Aided Design and In-Vivo Validation of a Cross-Reactive Peptide Based Multi-Epitope Vaccine Targeting Multiple Serotypes of Dengue Virus

“…Further, a plethora of immunoinformatics based studies are available in literature in the context of designing DENV vaccine where various research groups have been working on identification of epitopes from various structural and non-structural proteins from DENV virus (21)(22)(23)(24). In particular, identification of highly conserved amino acid sequences for the entire DENV proteome was performed by Khan and coworkers (25) where they identified highly conserved and immune relevant DENV sequences that were common across the four serotypes and have direct implications in design of tetravalent vaccine (26).…”

Screening Novel Vaccine Candidates for Leishmania Donovani by Combining Differential Proteomics and Immunoinformatics Analysis

“…It is prevalent that amino acid sequences are subjected to the predictions of helper T lymphocyte, cytotoxic T lymphocyte, and B cell epitopes, which saves lots of time and cost for vaccine research ( 18 ). Through the prediction of the epitope, many studies usually combined plenty of epitopes from different target proteins to construct multi-epitope vaccines, such as COVID-19, Leishmania , and Schistosoma ( 2 , 19 , 20 ). However, few studies have used bioinformatics to discover novel proteins of vaccine potential.…”