Accurate Transfer Efficiencies, Distance Distributions, and Ensembles of Unfolded and Intrinsically Disordered Proteins From Single-Molecule FRET

• Published in: Methods in enzymology Vol. 611; p. 287
• Main Authors: Holmstrom, Erik D, Holla, Andrea, Zheng, Wenwei, Nettels, Daniel, Best, Robert B, Schuler, Benjamin
• Format: Journal Article
• Language: English
• Published: United States 2018
• Subjects: Algorithms; Animals; Bayes Theorem; Equipment Design; Fluorescence Resonance Energy Transfer - instrumentation; Fluorescence Resonance Energy Transfer - methods; Humans; Intrinsically Disordered Proteins - chemistry; Models, Molecular; Protein Aggregates; Protein Conformation; Protein Unfolding; Förster resonance energy transfer; Polymers; Intrinsically disordered proteins; Single-molecule spectroscopy; Molecular simulations
• ISSN: 1557-7988
• DOI: 10.1016/bs.mie.2018.09.030

Intrinsically disordered proteins (IDPs) sample structurally diverse ensembles. Characterizing the underlying distributions of conformations is a key step toward understanding the structural and functional properties of IDPs. One increasingly popular method for obtaining quantitative information on intramolecular distances and distributions is single-molecule Förster resonance energy transfer (FRET). Here we describe two essential elements of the quantitative analysis of single-molecule FRET data of IDPs: the sample-specific calibration of the single-molecule instrument that is required for determining accurate transfer efficiencies, and the use of state-of-the-art methods for inferring accurate distance distributions from these transfer efficiencies. First, we illustrate how to quantify the correction factors for instrument calibration with alternating donor and acceptor excitation measurements of labeled samples spanning a wide range of transfer efficiencies. Second, we show how to infer distance distributions based on suitably parameterized simple polymer models, and how to obtain conformational ensembles from Bayesian reweighting of molecular simulations or from parameter optimization in simplified coarse-grained models.