Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 265

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Local Structure in Spider Dragline Silk Investigated by Two-Dimensional Spin-Diffusion Nuclear Magnetic Resonance

Open access
Kümmerlen, J., van Beek, J. D., Vollrath, F., Meier, B. H.·1996·Macromolecules

Abstract

The local structure of dragline silk from the spider Nephila madagascariensis is investigated by solid-state nuclear magnetic resonance. Two-dimensional (2D) spin-diffusion experiments show that the alanine-rich domains of the protein form β-sheet structures in agreement with one-dimensional NMR results from a different species of the genus Nephila (Simons, A.; Ray, E.; Jelinski, L. W. Macromolecules 1994, 27, 5235) but at variance with diffraction results. The microstructure of the glycine-rich domains is found to be ordered. The simplest model that explains the experimental findings is a 3 1 -helical structure. Random coils, planar β-sheets, and α-helical conformations are not found in significant amounts in the glycine-rich domains. This observation may help to explain the extraordinary mechanical properties of this silk, because 3 1 -helices can form interhelix hydrogen bonds.

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/ma951098i

Cites

1 of 1 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

Cited by

See all 265

Metadata

Authors
Kümmerlen, J., van Beek, J. D., Vollrath, F., & Meier, B. H.
Venue
Macromolecules
Published
1996-01-01
Volume
29
Issue
8
Pages
2920-2928
ISSN
  • 0024-9297 (ISSN-L)
  • 1520-5835
OpenAlex
W2096018585
Cited by
265
References
1
FWCI
11.62
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: Local Structure in Spider Dragline Silk Investigated by Two-Dimensional Spin-Diffusion Nuclear Magnetic Resonance. https://app.cochat.ai/papers/10.1021/ma951098i
The paper
Kümmerlen, J., van Beek, J. D., Vollrath, F., & Meier, B. H. (1996). Local Structure in Spider Dragline Silk Investigated by Two-Dimensional Spin-Diffusion Nuclear Magnetic Resonance. Macromolecules. https://doi.org/10.1021/ma951098i

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.