ArticleBiophysical journal2018
Confidence Analysis of DEER Data and Its Structural Interpretation with Ensemble-Biased Metadynamics.
Article in Biophysical journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Large-scale protein conformational transitions revealed by weighted ensemble simulations and EPR.Chemical science · 2026Article
- RNA binding and coacervation promote preservation of peptide form and function across the heterochiral-homochiral divide.Protein science : a publication of the Protein Society · 2025Article
- Modeling protein conformational ensembles by guiding AlphaFold2 with Double Electron Electron Resonance (DEER) distance distributions.Nature communications · 2025Article
- Protein Modeling with DEER Spectroscopy.Annual review of biophysics · 2025Review
- Expanded Functionality and Portability for the Colvars Library.The journal of physical chemistry. B · 2024Article
- Bayesian Probabilistic Inference of Nonparametric Distance Distributions in DEER Spectroscopy.The journal of physical chemistry. A · 2024Article
- Review
- Deconvoluting Monomer- and Dimer-Specific Distance Distributions between Spin Labels in a Monomer/Dimer Mixture UsingJournal of the American Chemical Society · 2024Article
- Comprehensive characterization of polyproline tri-helix macrocyclic nanoscaffolds for predictive ligand positioning.Nanoscale advances · 2024Article
- Cucurbit[7]uril Enhances Distance Measurements of Spin-Labeled Proteins.Journal of the American Chemical Society · 2023Article
- Asymmetric conformations and lipid interactions shape the ATP-coupled cycle of a heterodimeric ABC transporter.Nature communications · 2023Article
- Structural Insights into the Binding and Degradation Mechanisms of Protoporphyrin IX by the Translocator Protein TSPO.JACS Au · 2023Article
- SARS-CoV-2 fusion peptide sculpting of a membrane with insertion of charged and polar groups.Structure (London, England : 1993) · 2023Article
- Integrated AlphaFold2 and DEER investigation of the conformational dynamics of a pH-dependent APC antiporter.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- DEER Data Analysis Software: A Comparative Guide.Frontiers in molecular biosciences · 2022Article
- OOP-ESEEM Spectroscopy: Accuracies of Distances of Spin-Correlated Radical Pairs in Biomolecules.Frontiers in molecular biosciences · 2022Review
- Benchmark Test and Guidelines for DEER/PELDOR Experiments on Nitroxide-Labeled Biomolecules.Journal of the American Chemical Society · 2021Article
- Protein functional dynamics from the rigorous global analysis of DEER data: Conditions, components, and conformations.The Journal of general physiology · 2021Article
- Statistical analysis of ENDOR spectra.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Methodology for rigorous modeling of protein conformational changes by Rosetta using DEER distance restraints.PLoS computational biology · 2021Article
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Authors and funding
5 authors.
Funding
Abstract
Given its ability to measure multicomponent distance distributions between electron-spin probes, double electron-electron resonance (DEER) spectroscopy has become a leading technique to assess the structural dynamics of biomolecules. However, methodologies to evaluate the statistical error of these distributions are not standard, often hampering a rigorous interpretation of the experimental results. Distance distributions are often determined from the experimental DEER data through a mathematical method known as Tikhonov regularization, but this approach makes rigorous error estimates difficult. Here, we build upon an alternative, model-based approach in which the distance probability distribution is represented as a sum of Gaussian components, and use propagation of errors to calculate an associated confidence band. Our approach considers all sources of uncertainty, including the experimental noise, the uncertainty in the fitted background signal, and the limited time span of the data collection. The resulting confidence band reveals the most and least reliable features of the probability distribution, thereby informing the structural interpretation of DEER experiments. To facilitate this interpretation, we also generalize the molecular simulation method known as ensemble-biased metadynamics (EBMetaD). This method, originally designed to generate maximal-entropy structural ensembles consistent with one or more probability distributions, now also accounts for the uncertainty in those target distributions exactly as dictated by their confidence bands. After careful benchmarks, we demonstrate the proposed techniques using DEER results from spin-labeled T4 lysozyme.
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