The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains.
Abstract
A method to predict the relative binding strengths of all possible nonapeptides to the MHC class I molecule HLA-A2 has been developed based on experimental peptide binding data. These data indicate that, for most peptides, each side-chain of the peptide contributes a certain amount to the stability of the HLA-A2 complex that is independent of the sequence of the peptide. To quantify these contributions, the binding data from a set of 154 peptides were combined together to generate a table containing 180 coefficients (20 amino acids x 9 positions), each of which represents the contribution of one particular amino acid residue at a specified position within the peptide to binding to HLA-A2. Eighty peptides formed stable HLA-A2 complexes, as assessed by measuring the rate of dissociation of beta 2m. The remaining 74 peptides formed complexes that had a half-life of beta 2m dissociation of less than 5 min at 37 degrees C, or did not bind to HLA-A2, and were included because they could be used to constrain the values of some of the coefficients. The "theoretical" binding stability (calculated by multiplying together the corresponding coefficients) matched the experimental binding stability to within a factor of 5. The coefficients were then used to calculate the theoretical binding stability for all the previously identified self or antigenic nonamer peptides known to bind to HLA-A2. The binding stability for all other nonamer peptides that could be generated from the proteins from which these peptides were derived was also predicted. In every case, the previously described HLA-A2 binding peptides were ranked in the top 2% of all possible nonamers for each source protein. Therefore, most biologically relevant nonamer peptides should be identifiable using the table of coefficients. We conclude that the side-chains of most nonamer peptides to the first approximation bind independently of one another to the HLA-A2 molecule.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
STRUCTURE, FUNCTION, AND DIVERSITY OF CLASS I MAJOR HISTOCOMPATIBILITY COMPLEX MOLECULES
Bjorkman, P. J., & Parham, P. (1990) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.59.070190.001345 · Cited by 700
Cited by
Epitope Landscape in Breast and Colorectal Cancer
Segal, N. H., Parsons, D. W., Peggs, K. S., Velculescu, V., Kinzler, K. W., Vogelstein, B., & Allison, J. P. (2008) · Cancer Research · doi:10.1158/0008-5472.can-07-3095 · Cited by 416
Immunological aspects of experimental allergic encephalomyelitis and multiple sclerosis
Martin, R., McFarland, H. F., & Boggs, J. M. (1995) · Critical Reviews in Clinical Laboratory Sciences · doi:10.3109/10408369509084683 · Cited by 376
Buus, S., Lauemøller, S. L., Worning, P., Kesmir, C., Frimurer, T., Corbet, S., Fomsgaard, A., Hilden, J., Holm, A., & Brunak, S. (2003) · Tissue Antigens · doi:10.1034/j.1399-0039.2003.00112.x · Cited by 329
Cytotoxic T cell immunity against telomerase reverse transcriptase in humans
Minev, B., Hipp, J., Firat, H., Schmidt, J. D., Langlade-Demoyen, P., & Zanetti, M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.070560797 · Cited by 255
Peptide‐based therapeutic cancer vaccine: Current trends in clinical application
Liu, W., Tang, H., Li, L., Wang, X., Yu, Z., & Li, J. (2021) · Cell Proliferation · doi:10.1111/cpr.13025 · Cited by 200
Metadata
- Authors
- Parker, K. C., Bednarek, M. A., & Coligan, J. E.
- Venue
- The Journal of Immunology
- Publisher
- Oxford University Press (OUP)
- Published
- 1994-01-01
- Volume
- 152
- Issue
- 1
- Pages
- 163-175
- ISSN
- 0022-1767 (ISSN-L)
- 1550-6606
- OpenAlex
- W2166831581
- Cited by
- 1,370
- References
- 1
- FWCI
- 6.86
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. https://app.cochat.ai/papers/10.4049/jimmunol.152.1.163
- The paper
- Parker, K. C., Bednarek, M. A., & Coligan, J. E. (1994). Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. The Journal of Immunology. https://doi.org/10.4049/jimmunol.152.1.163
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.