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NMR Analysis of Protein Folding Interaction Networks

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Part of the Methods in Molecular Biology book series (MIMB,volume 2376)

Abstract

Theory and experimental evidence unequivocally indicate that protein folding is far more complex than the two-state (all-or-none) model that is usually assumed in the analysis of folding experiments. Proteins tend to fold hierarchically by forming secondary structure elements, followed by supersecondary arrangements, and other intermediate states that ultimately adopt the native tertiary fold as a result of a delicate balance between interatomic interactions and entropic contributions. However, small proteins with simple folds typically follow downhill folding, characterized by very small energetic barriers (<3 RT) that allow multiple protein conformations to be populated along the folding path down the free energy landscape, reaching the native fold at the lowest energy level.

Here we describe the use of solution-state nuclear magnetic resonance (NMR) for the analysis of protein folding interaction networks at atomic resolution. The assignment of NMR spectra acquired at different unfolding conditions provides hundreds of atomic unfolding curves that are analyzed to infer the network of folding interactions. The method is particularly useful to study small proteins that fold autonomously in the sub-millisecond timescale. The information obtained from the application of this method can potentially unveil the basic relationships between protein structure and folding.

Key words

  • Protein folding
  • Nuclear magnetic resonance
  • Interaction networks
  • Minimal cooperativity

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Acknowledgments

The author acknowledges support from the NSF-CREST Center for Cellular and Biomolecular Machines at the University of California, Merced (NSF-HRD-1547848).

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Correspondence to Eva de Alba .

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de Alba, E. (2022). NMR Analysis of Protein Folding Interaction Networks. In: Muñoz, V. (eds) Protein Folding. Methods in Molecular Biology, vol 2376. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1716-8_10

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  • DOI: https://doi.org/10.1007/978-1-0716-1716-8_10

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1715-1

  • Online ISBN: 978-1-0716-1716-8

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