Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 310

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis.

Open access
Sette, A, Buus, S, Appella, E, Smith, J A, Chesnut, R, Miles, C, Colon, S M, Grey, H M·1989·Proceedings of the National Academy of Sciences

Abstract

We have previously experimentally analyzed the structural requirements for interaction between peptide antigens and mouse major histocompatibility complex (MHC) molecules of the d haplotype. We describe here two procedures devised to predict specifically the capacity of peptide molecules to interact with these MHC class II molecules (IAd and IEd). The accuracy of these procedures has been tested on a large panel of synthetic peptides of eukaryotic, prokaryotic, and viral origin, and also on a set of overlapping peptides encompassing the entire staphylococcal nuclease molecule. For both sets of peptides, IAd and IEd binding was successfully predicted in approximately 75% of the cases. This suggests that definition of such sequence "motifs" could be of general use in predicting potentially immunogenic peptide regions within proteins.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.86.9.3296

Cites

10 of 10 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 10 references

Cited by

See all 310

Metadata

Authors
Sette, A., Buus, S., Appella, E., Smith, J. A., Chesnut, R., Miles, C., Colon, S. M., & Grey, H. M.
Venue
Proceedings of the National Academy of Sciences
Published
1989-05
Volume
86
Issue
9
Pages
3296-3300
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2035194338
Cited by
310
References
10
FWCI
5.70
Type
journal article
Language
en
Open access
green

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: Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis. https://app.cochat.ai/papers/10.1073/pnas.86.9.3296
The paper
Sette, A., Buus, S., Appella, E., Smith, J. A., Chesnut, R., Miles, C., Colon, S. M., & Grey, H. M. (1989). Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.86.9.3296

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.