Abstract
Peptide-based vaccines are an appealing strategy which involves usage of short synthetic peptides to engineer a highly targeted immune response. These short synthetic peptides contain potential T- and B-cell epitopes. Experimental approaches in identifying these epitopes are time-consuming and expensive; hence immunoinformatics approach came into picture. Immuninformatics approach involves epitope prediction tools, molecular docking, and population coverage analysis in design of desired immunogenic peptides. In order to overcome the antigenic variation of viruses, conserved regions are targeted to find the potential epitopes. The present chapter demonstrates the use of immunoinformatics approach to select potential peptide containing multiple T- (CD8+ and CD4+) and B-cell epitopes from Avian H3N2 M1 Protein. Further, molecular docking (to analyse HLA-peptide interaction) and population coverage analysis have been used to verify the potential of peptide to be presented by polymorphic HLA molecules. In silico approach of epitope prediction has proven to be successful methodology in screening the putative epitopes among numerous possible vaccine targets in a given protein.
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Lohia, N., Baranwal, M. (2020). An Immunoinformatics Approach in Design of Synthetic Peptide Vaccine Against Influenza Virus. In: Tomar, N. (eds) Immunoinformatics. Methods in Molecular Biology, vol 2131. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0389-5_11
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DOI: https://doi.org/10.1007/978-1-0716-0389-5_11
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