Unfolded states under folding conditions accommodate sequence-specific conformational preferences with random coil-like dimensions
Holehouse, Alex S.
Carrico, Isaac S.
Pappu, Rohit V.
Raleigh, Daniel P.
UMass Chan AffiliationsDepartment of Biochemistry and Molecular Pharmacology
Document TypeJournal Article
Amino Acids, Peptides, and Proteins
MetadataShow full item record
AbstractProteins are marginally stable molecules that fluctuate between folded and unfolded states. Here, we provide a high-resolution description of unfolded states under refolding conditions for the N-terminal domain of the L9 protein (NTL9). We use a combination of time-resolved Forster resonance energy transfer (FRET) based on multiple pairs of minimally perturbing labels, time-resolved small-angle X-ray scattering (SAXS), all-atom simulations, and polymer theory. Upon dilution from high denaturant, the unfolded state undergoes rapid contraction. Although this contraction occurs before the folding transition, the unfolded state remains considerably more expanded than the folded state and accommodates a range of local and nonlocal contacts, including secondary structures and native and nonnative interactions. Paradoxically, despite discernible sequence-specific conformational preferences, the ensemble-averaged properties of unfolded states are consistent with those of canonical random coils, namely polymers in indifferent (theta) solvents. These findings are concordant with theoretical predictions based on coarse-grained models and inferences drawn from single-molecule experiments regarding the sequence-specific scaling behavior of unfolded proteins under folding conditions.
Proc Natl Acad Sci U S A. 2019 Jun 18;116(25):12301-12310. doi: 10.1073/pnas.1818206116. Epub 2019 Jun 5. Link to article on publisher's site
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/41112
RightsCopyright © 2019 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial- NoDerivatives License 4.0 (CC BY-NC-ND).
Except where otherwise noted, this item's license is described as Copyright © 2019 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial- NoDerivatives License 4.0 (CC BY-NC-ND).