ArticleJournal of structural biology2011
RosettaEPR: an integrated tool for protein structure determination from sparse EPR data.
Article in Journal of structural biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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72 citing papers in PubMed.
- Large-scale protein conformational transitions revealed by weighted ensemble simulations and EPR.Chemical science · 2026Article
- 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
- Modeling of Cu(II)-based protein spin labels using rotamer libraries.Physical chemistry chemical physics : PCCP · 2024Article
- Efficient determination of the accessible conformation space of multi-domain complexes based on EPR PELDOR data.Journal of biomolecular NMR · 2023Article
- Direct observation of negative cooperativity in a detoxification enzyme at the atomic level by Electron Paramagnetic Resonance spectroscopy and simulation.Protein science : a publication of the Protein Society · 2023Article
- chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling.PLoS computational biology · 2023Article
- Interdomain Linkers Regulate Histidine Kinase Activity by Controlling Subunit Interactions.Biochemistry · 2022Article
- Structure of membrane diacylglycerol kinase in lipid bilayers.Communications biology · 2021Article
- How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations.Computational and structural biotechnology journal · 2021Review
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Characterization of the ExoU activation mechanism using EPR and integrative modeling.Scientific reports · 2020Article
- High-throughput mutagenesis reveals unique structural features of human ADAR1.Nature communications · 2020Article
- Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement.Journal of chemical information and modeling · 2020Article
- Cu2+-based distance measurements by pulsed EPR provide distance constraints for DNA backbone conformations in solution.Nucleic acids research · 2020Article
- Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction.Biophysical journal · 2020Article
- Improving mass spectrometry analysis of protein structures with arginine-selective chemical cross-linkers.Nature communications · 2019Article
- Predicting Protein Complex Structure from Surface-Induced Dissociation Mass Spectrometry Data.ACS central science · 2019Article
- Hybrid Refinement of Heterogeneous Conformational Ensembles Using Spectroscopic Data.The journal of physical chemistry letters · 2019Article
- Utility of Covalent Labeling Mass Spectrometry Data in Protein Structure Prediction with Rosetta.Journal of chemical theory and computation · 2019Article
12 more citing papers are in PubMed but not listed here.
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4 authors.
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Abstract
Site-directed spin labeling electron paramagnetic resonance (SDSL-EPR) is often used for the structural characterization of proteins that elude other techniques, such as X-ray crystallography and nuclear magnetic resonance (NMR). However, high-resolution structures are difficult to obtain due to uncertainty in the spin label location and sparseness of experimental data. Here, we introduce RosettaEPR, which has been designed to improve de novo high-resolution protein structure prediction using sparse SDSL-EPR distance data. The "motion-on-a-cone" spin label model is converted into a knowledge-based potential, which was implemented as a scoring term in Rosetta. RosettaEPR increased the fractions of correctly folded models ( [Formula: see text] <7.5Å) and models accurate at medium resolution ( [Formula: see text] <3.5Å) by 25%. The correlation of score and model quality increased from 0.42 when using no restraints to 0.51 when using bounded restraints and again to 0.62 when using RosettaEPR. This allowed for the selection of accurate models by score. After full-atom refinement, RosettaEPR yielded a 1.7Å model of T4-lysozyme, thus indicating that atomic detail models can be achieved by combining sparse EPR data with Rosetta. While these results indicate RosettaEPR's potential utility in high-resolution protein structure prediction, they are based on a single example. In order to affirm the method's general performance, it must be tested on a larger and more versatile dataset of proteins.
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