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Cited by 975

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Speeding molecular recognition by using the folding funnel: The fly-casting mechanism

Open access
Shoemaker, Benjamin A., Portman, John J., Wolynes, Peter G.·2000·Proceedings of the National Academy of Sciences

Abstract

Protein folding and binding are kindred processes. Many proteins in the cell are unfolded, so folding and function are coupled. This paper investigates how binding kinetics is influenced by the folding of a protein. We find that a relatively unstructured protein molecule can have a greater capture radius for a specific binding site than the folded state with its restricted conformational freedom. In this scenario of binding, the unfolded state binds weakly at a relatively large distance followed by folding as the protein approaches the binding site: the “fly-casting mechanism.” We illustrate this scenario with the hypothetical kinetics of binding a single repressor molecule to a DNA site and find that the binding rate can be significantly enhanced over the rate of binding of a fully folded protein.

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Crossref · 10.1073/pnas.160259697

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Metadata

Authors
Shoemaker, B. A., Portman, J. J., & Wolynes, P. G.
Venue
Proceedings of the National Academy of Sciences
Published
2000-07-25
Volume
97
Issue
16
Pages
8868-8873
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2034299708
Cited by
975
References
6
FWCI
4.06
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Speeding molecular recognition by using the folding funnel: The fly-casting mechanism. https://app.cochat.ai/papers/10.1073/pnas.160259697
The paper
Shoemaker, B. A., Portman, J. J., & Wolynes, P. G. (2000). Speeding molecular recognition by using the folding funnel: The fly-casting mechanism. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.160259697

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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.