Dataset Information

Design of a multi-epitope protein as a subunit vaccine against lumpy skin disease using an immunoinformatics approach.

ABSTRACT: Lumpy skin disease (LSD) is a transboundary viral disease of cattle that causes substantial economic loss globally. There is no specific treatment and subunit vaccine for this disease to date. Reports of the global spread of this disease are worrisome. We designed a multi-epitope protein using an immunoinformatics approach in this study. We analyzed the proteome of LSDV and found 32 structural/surface proteins. Four of these 32 proteins were predicted as antigenic and non-homologous to bovine and highly conserved in 26 LSDV isolates. The predicted B-cell epitopes and CTL epitopes were stitched together with the help of an AAY linker leading to the formation of a multi-epitope protein. The in silico study revealed that the modeled subunit vaccine candidate and TLR4 receptor interact with high affinity. This interaction was also found to be stable using a molecular dynamics simulation study. Our study demonstrates a leap towards developing a subunit vaccine against LSD.

SUBMITTER: Kar PP

PROVIDER: S-EPMC9653426 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Design of a multi-epitope protein as a subunit vaccine against lumpy skin disease using an immunoinformatics approach.

Kar Prajna Parimita PP Araveti Prasanna Babu PB Kuriakose Akshay A Srivastava Anand A

Scientific reports 20221112 1

Lumpy skin disease (LSD) is a transboundary viral disease of cattle that causes substantial economic loss globally. There is no specific treatment and subunit vaccine for this disease to date. Reports of the global spread of this disease are worrisome. We designed a multi-epitope protein using an immunoinformatics approach in this study. We analyzed the proteome of LSDV and found 32 structural/surface proteins. Four of these 32 proteins were predicted as antigenic and non-homologous to bovine an ...[more]

PMID: 36371522

Similar Datasets

Project description:Tuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette-Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine's physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system's intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine's efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.

Dataset Information

Design of a multi-epitope protein as a subunit vaccine against lumpy skin disease using an immunoinformatics approach.

Publications

Design of a multi-epitope protein as a subunit vaccine against lumpy skin disease using an immunoinformatics approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets