ArticleComputational biology and chemistry2013
A combination of epitope prediction and molecular docking allows for good identification of MHC class I restricted T-cell epitopes.
Article in Computational biology and chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 17 citations in OpenAlex.
- A High-Coverage Epitope-Based Vaccine Design for EIAV Envelope Polyprotein Using an Immunoinformatic Approach.Veterinary sciences · 2026Article
- A CombinatorialBio-protocol · 2021Article
- AI Aided Design of Epitope-Based Vaccine for the Induction of Cellular Immune Responses Against SARS-CoV-2.Frontiers in genetics · 2021Article
- A Mouse Model of PPRV Infection for Elucidating Protective and Pathological Roles of Immune Cells.Frontiers in immunology · 2021Article
- Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2.Molecules (Basel, Switzerland) · 2020Article
- Predicting Promiscuous T Cell Epitopes for Designing a Vaccine Against Streptococcus pyogenes.Applied biochemistry and biotechnology · 2019Article
- Identification and evaluation of the novel immunodominant antigen Rv2351c from Mycobacterium tuberculosis.Emerging microbes & infections · 2017Article
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1 author at 1 institution in 1 country.
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Abstract
In silico identification of T-cell epitopes is emerging as a new methodology for the study of epitope-based vaccines against viruses and cancer. In order to improve accuracy of prediction, we designed a novel approach, using epitope prediction methods in combination with molecular docking techniques, to identify MHC class I restricted T-cell epitopes. Analysis of the HIV-1 p24 protein and influenza virus matrix protein revealed that the present approach is effective, yielding prediction accuracy of over 80% with respect to experimental data. Subsequently, we applied such a method for prediction of T-cell epitopes in SARS coronavirus (SARS-CoV) S, N and M proteins. Based on available experimental data, the prediction accuracy is up to 90% for S protein. We suggest the use of epitope prediction methods in combination with 3D structural modelling of peptide-MHC-TCR complex to identify MHC class I restricted T-cell epitopes for use in epitope based vaccines like HIV and human cancers, which should provide a valuable step forward for the design of better vaccines and may provide in depth understanding about activation of T-cell epitopes by MHC binding peptides.
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