ArticleImmunogenetics2015
Role of peptide processing predictions in T cell epitope identification: contribution of different prediction programs.
Article in Immunogenetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 46 citations in OpenAlex.
- Toward next-generation therapeutic HPV vaccines: A review on expanding the antigen repertoire and an integrated bioinformatics selection framework.Human vaccines & immunotherapeutics · 2026Review
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Substrate secondary structure is associated with proteasomal cleavage propensity.Frontiers in bioinformatics · 2026Article
- Advances in Therapeutic Cancer Vaccines, Their Obstacles, and Prospects Toward Tumor Immunotherapy.Molecular biotechnology · 2025Review
- Review
- In Silico Tools for Predicting Novel Epitopes.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Therapeutic cancer vaccines: advancements, challenges, and prospects.Signal transduction and targeted therapy · 2023Review
- Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy.Frontiers in immunology · 2023Review
- The Importance of Being Presented: Target Validation by Immunopeptidomics for Epitope-Specific Immunotherapies.Frontiers in immunology · 2022Review
- Prediction and validation of murine MHC class I epitopes of the recombinant virus VSV-GP.Frontiers in immunology · 2022Article
- Immunoinformatic analysis of the whole proteome for vaccine design: An application toFrontiers in immunology · 2022Article
- Design of Personalized Neoantigen RNA Vaccines Against Cancer Based on Next-Generation Sequencing Data.Methods in molecular biology (Clifton, N.J.) · 2022Article
- In vitro proteasome processing of neo-splicetopes does not predict their presentation in vivo.eLife · 2021Article
- Review
- Large database for the analysis and prediction of spliced and non-spliced peptide generation by proteasomes.Scientific data · 2020Article
- POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction.Frontiers in immunology · 2020Article
- Neoantigens in Hematologic Malignancies.Frontiers in immunology · 2020Review
- Antigen processing and presentation in HIV infection.Molecular immunology · 2019Review
- Best practices for bioinformatic characterization of neoantigens for clinical utility.Genome medicine · 2019Review
- Systems Immunology: Learning the Rules of the Immune System.Annual review of immunology · 2018Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteolysis is the general term to describe the process of protein degradation into peptides. Proteasomes are the main actors in cellular proteolysis, and their activity can be measured in in vitro digestion experiments. However, in vivo proteolysis can be different than what is measured in these experiments if other proteases participate or if proteasomal activity is different in vivo. The in vivo proteolysis can be measured only indirectly, by the analysis of peptides presented on MHC-I molecules. MHC-I presented peptides are protected from further degradation, thus enabling an indirect view on the underlying in vivo proteolysis. The ligands presented on different MHC-I molecules enable different views on this process; in combination, they might give a complete picture. Based on in vitro proteasome-only digestions and MHC-I ligand data, different proteolysis predictors have been developed. With new in vitro digestion and MHC-I ligand data sets, we benchmarked how well these predictors capture in vitro proteasome-only activity and in vivo whole-cell proteolysis, respectively. Even though the in vitro proteasome digestion patterns were best captured by methods trained on such data (ProteaSMM and NetChop 20S), the in vivo whole-cell proteolysis was best predicted by a method trained on MHC-I ligand data (NetChop Cterm). Follow-up analysis showed that the likely source of this difference is the activity from proteases other than the proteasome, such as TPPII. This non-proteasomal in vivo activity is captured by NetChop Cterm and should be taken into account in MHC-I ligand predictions.
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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.