Reconstructing folding energy landscapes from splitting probability analysis of single-molecule trajectories

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DOIResolve DOI: http://doi.org/10.1073/pnas.1419490112
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TypeArticle
Journal titleProceedings of the National Academy of Sciences
ISSN0027-8424
1091-6490
Volume112
Issue23
Pages71837188
Subjectsingle-molecule biophysics; force spectroscopy; nucleic acid folding; protein folding; optical tweezers
AbstractStructural self-assembly in biopolymers, such as proteins and nucleic acids, involves a diffusive search for the minimum-energy state in a conformational free-energy landscape. The likelihood of folding proceeding to completion, as a function of the reaction coordinate used to monitor the transition, can be described by the splitting probability, pfold(x). Pfold encodes information about the underlying energy landscape, and it is often used to judge the quality of the reaction coordinate. Here, we show how pfold can be used to reconstruct energy landscapes from single-molecule folding trajectories, using force spectroscopy measurements of single DNA hairpins. Calculating pfold(x) directly from trajectories of the molecular extension measured for hairpins fluctuating in equilibrium between folded and unfolded states, we inverted the result expected from diffusion over a 1D energy landscape to obtain the implied landscape profile. The results agreed well with the landscapes reconstructed by established methods, but, remarkably, without the need to deconvolve instrumental effects on the landscape, such as tether compliance. The same approach was also applied to hairpins with multistate folding pathways. The relative insensitivity of the method to the instrumental compliance was confirmed by simulations of folding measured with different tether stiffnesses. This work confirms that the molecular extension is a good reaction coordinate for these measurements, and validates a powerful yet simple method for reconstructing landscapes from single-molecule trajectories.
Publication date
PublisherNational Academy of Sciences
LanguageEnglish
AffiliationNational Institute for Nanotechnology; National Research Council Canada
Peer reviewedYes
NPARC number23001596
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Record identifier923586bf-0ebc-40e3-9f25-b60257b65d82
Record created2017-03-09
Record modified2017-03-09
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