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Updated: May 7, 2025
A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
Designing multi-epitope vaccines against Echinococcus granulosus: an in-silico study using immuno-informatics
Jadoon Khan1,2,3, Asma Sadiq4, May M Alrashed5
1Faculty of Biological Sciences, Department of Microbiology, Quaid I Azam University Islamabad, Islamabad, Pakistan. jadoonkhan@bs.qau.edu.pk.
Abstract:
Cystic echinococcosis (CE) is a worldwide zoonotic public health issue. The reasons for this include a lack of specific therapy options, increasing antiparasitic drug resistance, a lack of control strategies, and the absence of an approved vaccine. The aim of the current study is to develop a multiepitope vaccine against CE by in-silico identification and using different Antigen B subunits. The five Echinococcus granulosus antigen B (EgAgB) subunits were examined for eminent antigenic epitopes, and then the best B-cell and Major Histocompatibility Complex MHC-binding epitopes were predicted. Most significant epitopes were combined to create an effective multi-epitope vaccine, which was then validated by testing its secondary and tertiary structures, physicochemical properties, and molecular dynamics (MD) modelling. A multi-epitope vaccine construct of 483 amino acid sequences was designed. It contains B-cell, Helper T Lymphocyte (HTL), and Cytotoxic T Lymphocyte (CTL) epitopes as well as the appropriate adjuvant and linker molecules. The resultant vaccinal construct had a GDT-HA value of 0.9725, RMSD of 0.299, MolProbity of 1.891, Clash score of 13.1, Poor rotamers of 0.9, and qualifying features with Rama favoured of 89.9. It was also highly immunogenic and less allergic. The majority of the amino acids were positioned in the Ramachandran plot's favourable area, and during the molecular dynamic simulation at 100 ns, no notable structural abnormalities were noticed. The resultant construct was significantly expressed and received good endorsement in the pIB2-SEC13-mEGFP expressional vector. In conclusion, the current in-silico multi-epitope vaccine may be evaluated in-vitro, in-vivo, and in clinical trials as an immunogenic vaccine model. It can also play a vital role in preventing this zoonotic parasite infection.
Insights
Researchers developed a novel multi-epitope vaccine against cystic echinococcosis (CE) using in-silico methods. This promising vaccine candidate shows high immunogenicity and structural stability, offering a potential new strategy to combat this global zoonotic disease.
Area of Science:
- Parasitology
- Vaccinology
- Bioinformatics
Background:
- Cystic echinococcosis (CE) is a significant global zoonotic disease with limited treatment options and no approved vaccine.
- Antiparasitic drug resistance and a lack of effective control strategies exacerbate the public health burden of CE.
Purpose of the Study:
- To design and computationally validate a novel multi-epitope vaccine against Cystic Echinococcosis (CE).
- To identify and combine key antigenic epitopes from Echinococcus granulosus Antigen B (EgAgB) subunits for vaccine development.
Main Methods:
- In-silico identification and selection of B-cell and Major Histocompatibility Complex (MHC)-binding epitopes from five EgAgB subunits.
- Computational construction of a multi-epitope vaccine incorporating B-cell, Helper T Lymphocyte (HTL), and Cytotoxic T Lymphocyte (CTL) epitopes, along with adjuvant and linker molecules.
- Validation of the vaccine construct's structural integrity, physicochemical properties, immunogenicity, and allergenicity using molecular dynamics (MD) simulations and structural analysis tools.
Main Results:
- A 483-amino acid multi-epitope vaccine construct was designed, integrating critical epitopes and validation parameters.
- The vaccine construct demonstrated favorable structural stability (GDT-HA: 0.9725, RMSD: 0.299), high immunogenicity, and low predicted allergenicity.
- Molecular dynamics simulations confirmed structural integrity over 100 ns, and the construct showed good expression potential in a relevant vector.
Conclusions:
- The in-silico designed multi-epitope vaccine is a promising immunogenic candidate for CE prevention.
- Further in-vitro, in-vivo, and clinical evaluations are warranted to assess its efficacy as a vaccine model.
- This computational approach offers a viable strategy for developing new vaccines against zoonotic parasitic infections like CE.
