ArticlePLoS computational biology2013
Properties of MHC class I presented peptides that enhance immunogenicity.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 514 papers, 1 of them a synthesis that pooled it.
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Who cites it
514 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analysis of experimentally validated neo-epitopes: patterns, biases, and opportunities.Cancer immunology, immunotherapy : CII · 2025Pooled it
- Targeting Amastigote and Trypomastigote Phases: Multi-Epitope Vaccine Strategy Against Trypanosoma cruzi.Biotechnology and applied biochemistry · 2026Article
- Review
- TrambaHLApan: A Transformer and Mamba-based Neoantigen Prediction Method Considering both Antigen Presentation and Immunogenicity.Interdisciplinary sciences, computational life sciences · 2026Article
- Central T cell tolerance from sparse peptide sampling.Science advances · 2026Article
- Article
- Structural Basis for the Immunological Paradox of a High-Affinity Yet Non-Immunogenic MHC-I Epitope fromBiology · 2026Article
- Immuno-Informatics Design of Multi-Epitope Vaccine Candidate AgainstHealth science reports · 2026Article
- What Does the Shape Space of T Cell Epitopes Look Like?Immunological reviews · 2026Review
- Computational structural dynamics and immunoinformatic analysis of EIEC IpaHMolecular diversity · 2026Article
- Cancer epitope prediction tools and analysis pipelines in CEDAR.Nucleic acids research · 2026Article
- Enhancing tumor T cell antigen prediction by integrating deep protein representations.BMC bioinformatics · 2026Article
- Cross-task interpretability through unified modeling reveals a universal shortcut bias in neoantigen prediction.Cell genomics · 2026Article
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Subtractive Proteomics and Immunoinformatics-Guided Design of a Multi-Epitope Vaccine Against Aspergillus fumigatus.Probiotics and antimicrobial proteins · 2026Article
- In silico design and evaluation of a candidate multiepitope Salmonella vaccine construct targeting broad-spectrum protection in poultry.BMC genomics · 2026Article
- Transfer learning for T-cell response prediction.BMC bioinformatics · 2026Article
- Computational design and molecular characterization of a multi-epitope peptide vaccine targeting pancreatic cancer.Journal, genetic engineering & biotechnology · 2026Article
- Immunoinformatics-Driven Identification of Conserved Multi-Epitope Vaccine Candidates from PDI Protein of Leishmania Donovani for Visceral Leishmaniasis.Cell biochemistry and biophysics · 2026Article
- Combating Streptococcus agalactiae infections by designing a multi-epitope vaccine using molecular dynamic simulations.Journal, genetic engineering & biotechnology · 2026Article
454 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4-6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.
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Registered trials
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.