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Understanding the key factors that control the rate of β-hairpin folding

Open access
Du, Deguo, Zhu, Yongjin, Huang, Cheng-Yen, Gai, Feng·2004·Proceedings of the National Academy of Sciences

Abstract

Both turn sequence and interstrand hydrophobic side-chain–side-chain interaction have been suggested to be important determinants of β-hairpin stability. However, their roles in controlling the folding dynamics of β-hairpins have not been clearly determined. Herein, we investigated the structural stability and folding kinetics of a series of tryptophan zippers by static IR and CD spectroscopies and the IR temperature jump method. Our results support a β-hairpin folding mechanism wherein the rate-limiting event corresponds to the formation of the turn. We find that the logarithm of the folding rate depends linearly on the entropic change associated with the turn formation, where faster folding correlates with lower entropic cost. Moreover, a stronger turn-promoting sequence increases the stability of a β-hairpin primarily by increasing its folding rate, whereas a stronger hydrophobic cluster increases the stability of a β-hairpin primarily by decreasing its unfolding rate.

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Metadata

Authors
Du, D., Zhu, Y., Huang, C.-Y., & Gai, F.
Venue
Proceedings of the National Academy of Sciences
Published
2004-11
Volume
101
Issue
45
Pages
15915-15920
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2058198562
Cited by
195
References
0
FWCI
3.61
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Understanding the key factors that control the rate of β-hairpin folding. https://app.cochat.ai/papers/10.1073/pnas.0405904101
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Du, D., Zhu, Y., Huang, C.-Y., & Gai, F. (2004). Understanding the key factors that control the rate of β-hairpin folding. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0405904101

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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.