Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 159

The DOI matches its Crossref record.

Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales

Open access
Shi, Zhengshuang, Chen, Kang, Liu, Zhigang, Ng, Angela, Bracken, W. Clay, Kallenbach, Neville R.·2005·Proceedings of the National Academy of Sciences

Abstract

There is growing appreciation of the functional relevance of unfolded proteins in biology. However, unfolded states of proteins have proven inaccessible to the usual techniques for high-resolution structural and energetic characterization. Unfolded states are still generally conceived of as statistical coils, based on the pioneering work of Flory [(1969) Statistical Mechanics of Chain Molecules (Wiley, New York)] and Tanford [(1968) Adv. Protein Chem. 23, 121–282]. Recently, several lines of independent evidence have raised doubts about the random coil model and offer support for alternative views. Here, we show that polyproline II conformation is dominant in a host–guest peptide model AcGGXGGNH 2 (X ≠ glycine), in equilibrium predominantly with β-structure. This result is inconsistent with a random coil model and the general view that these peptides are unstructured. By calculating a set of apparent Δ G values from the measured coupling constants of the backbone amides, we can construct a polyproline II scale that correlates negatively with β-sheet scales.

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.0507124102

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 159

Metadata

Authors
Shi, Z., Chen, K., Liu, Z., Ng, A., Bracken, W. C., & Kallenbach, N. R.
Venue
Proceedings of the National Academy of Sciences
Published
2005-12-05
Volume
102
Issue
50
Pages
17964-17968
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1973783994
Cited by
159
References
0
FWCI
2.30
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: Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales. https://app.cochat.ai/papers/10.1073/pnas.0507124102
The paper
Shi, Z., Chen, K., Liu, Z., Ng, A., Bracken, W. C., & Kallenbach, N. R. (2005). Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0507124102

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.