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Cited by 228

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Observation of sequence specificity in the seeding of protein amyloid fibrils

Open access
Krebs, Mark R.H., Morozova‐Roche, Ludmilla A., Daniel, Katie, Robinson, Carol V., Dobson, Christopher M.·2004·Protein Science

Abstract

It is well established that the rate of formation of fibrils by amyloidogenic proteins is enhanced by the addition of preformed fibrils, a phenomenon known as seeding. We show that the efficiency of seeding fibril formation from solutions of hen lysozyme by a series of other proteins depends strongly on the similarity of their sequences. This observation is consistent with the importance of long‐range interactions in stabilizing the core structure of amyloid fibrils and may be associated with the existence of a species barrier observed in the transmissible spongiform encephalopathies. In addition, it is consistent with the observation of a single dominant type of protein in the deposits associated with each form of amyloid disease.

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Crossref · 10.1110/ps.04707004

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Metadata

Authors
Krebs, M. R. H., Morozova‐Roche, L. A., Daniel, K., Robinson, C. V., & Dobson, C. M.
Venue
Protein Science
Publisher
Wiley
Published
2004-07
Volume
13
Issue
7
Pages
1933-1938
ISSN
  • 0961-8368 (ISSN-L)
  • 1469-896X
OpenAlex
W2104849621
Cited by
228
References
2
FWCI
4.15
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Observation of sequence specificity in the seeding of protein amyloid fibrils. https://app.cochat.ai/papers/10.1110/ps.04707004
The paper
Krebs, M. R. H., Morozova‐Roche, L. A., Daniel, K., Robinson, C. V., & Dobson, C. M. (2004). Observation of sequence specificity in the seeding of protein amyloid fibrils. Protein Science. https://doi.org/10.1110/ps.04707004

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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.