ArticleJournal of computer-aided molecular design2002
Recovery of known T-cell epitopes by computational scanning of a viral genome.
Article in Journal of computer-aided molecular design, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 46 citations in OpenAlex.
- Screening and Identification of HBV Epitopes Restricted by Multiple Prevalent HLA-A Allotypes.Frontiers in immunology · 2022Article
- Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes.Current topics in medicinal chemistry · 2018Review
- T-cell epitope vaccine design by immunoinformatics.Open biology · 2013Review
- Article
- PeptX: using genetic algorithms to optimize peptides for MHC binding.BMC bioinformatics · 2011Article
- pDOCK: a new technique for rapid and accurate docking of peptide ligands to Major Histocompatibility Complexes.Immunome research · 2010Article
- SVMHC: a server for prediction of MHC-binding peptides.Nucleic acids research · 2006Article
- Modeling the bound conformation of Pemphigus vulgaris-associated peptides to MHC Class II DR and DQ alleles.Immunome research · 2006Article
- Association of chronic fatigue syndrome with human leucocyte antigen class II alleles.Journal of clinical pathology · 2005Article
- Processing sites are different in the generation of HLA-A2.1-restricted, T cell reactive tumor antigen epitopes and viral epitopes.International journal of immunopathology and pharmacologyArticle
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.