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Updated: Dec 26, 2025

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
Immunoinformatics and Epitope Prediction
Jayashree Ramana1, Kusum Mehla2
1Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, HP, India. ramana.jayashree@gmail.com.
Abstract:
With advancements in sequencing technologies, vast amount of experimental data has accumulated. Due to rapid progress in the development of bioinformatics tools and the accumulation of data, immunoinformatics or computational immunology emerged as a special branch of bioinformatics which utilizes bioinformatics approaches for understanding and interpreting immunological data. One extensively studied aspect of applied immunology involves using available databases and tools for prediction of B- and T-cell epitopes. B and T cells comprise two arms of adaptive immunity.This chapter first reviews the methodology we used for computational identification of B- and T-cell epitopes against enterotoxigenic Escherichia coli (ETEC). Then we discuss other databases of epitopes and analysis tools for T-cell and B-cell epitope prediction and vaccine design. The predicted peptides were analyzed for conservation and population coverage. HLA distribution analysis for predicted epitopes identified efficient MHC binders. Epitopes were further tested using computational docking studies to bind in MHC-I molecule cleft. The predicted epitopes were conserved and covered more than 80% of the world population.
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