Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 175

The DOI matches its Crossref record.

Structural Characterization of Proteins with an Attached ATCUN Motif by Paramagnetic Relaxation Enhancement NMR Spectroscopy

Donaldson, Logan W., Skrynnikov, Nikolai R., Choy, Wing-Yiu, Muhandiram, D. Ranjith, Sarkar, Bibudhendra, Forman-Kay, Julie D., Kay, Lewis E.·2001·Journal of the American Chemical Society

Abstract

The use of a short, three-residue Cu(2+)-binding sequence, the ATCUN motif, is presented as an approach for extracting long-range distance restraints from relaxation enhancement NMR spectroscopy. The ATCUN motif is prepended to the N-termini of proteins and binds Cu(2+) with a very high affinity. Relaxation rates of amide protons in ATCUN-tagged protein in the presence and absence of Cu(2+) can be converted into distance restraints and used for structure refinement by using a new routine, PMAG, that has been written for the structure calculation program CNS. The utility of the approach is demonstrated with an application to ATCUN-tagged ubiquitin. Excellent agreement between measured relaxation rates and those calculated on the basis of the X-ray structure of the protein have been obtained.

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 · 10.1021/ja011241p

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.

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

Cited by

See all 175

Metadata

Authors
Donaldson, L. W., Skrynnikov, N. R., Choy, W.-Y., Muhandiram, D. R., Sarkar, B., Forman-Kay, J. D., & Kay, L. E.
Venue
Journal of the American Chemical Society
Published
2001-09-15
Volume
123
Issue
40
Pages
9843-9847
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2046924261
Cited by
175
References
0
FWCI
3.79
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: Structural Characterization of Proteins with an Attached ATCUN Motif by Paramagnetic Relaxation Enhancement NMR Spectroscopy. https://app.cochat.ai/papers/10.1021/ja011241p
The paper
Donaldson, L. W., Skrynnikov, N. R., Choy, W.-Y., Muhandiram, D. R., Sarkar, B., Forman-Kay, J. D., & Kay, L. E. (2001). Structural Characterization of Proteins with an Attached ATCUN Motif by Paramagnetic Relaxation Enhancement NMR Spectroscopy. Journal of the American Chemical Society. https://doi.org/10.1021/ja011241p

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.