ArticleStructure (London, England : 1993)2019
Structural Characterization of Biomolecules through Atomistic Simulations Guided by DEER Measurements.
Article in Structure (London, England : 1993), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 28 citations in OpenAlex.
- ProGuide: a flexible framework for modeling global conformational rearrangements in proteins using DEER-derived distance restraints.bioRxiv : the preprint server for biology · 2025Article
- Protein Modeling with DEER Spectroscopy.Annual review of biophysics · 2025Review
- Allosteric substrate release by a sialic acid TRAP transporter substrate binding protein.Communications biology · 2024Article
- Expanded Functionality and Portability for the Colvars Library.The journal of physical chemistry. B · 2024Article
- On the function of TRAP substrate-binding proteins: Conformational variation of the sialic acid binding protein SiaP.The Journal of biological chemistry · 2024Article
- Review
- Conformational coupling of the sialic acid TRAP transporter HiSiaQM with its substrate binding protein HiSiaP.Nature communications · 2024Article
- Benchmark Test and Guidelines for DEER/PELDOR Experiments on Nitroxide-Labeled Biomolecules.Journal of the American Chemical Society · 2021Article
- Energy penalties enhance flexible receptor docking in a model cavity.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
- Interpreting Hydrogen-Deuterium Exchange Experiments with Molecular Simulations: Tutorials and Applications of the HDXer Ensemble Reweighting Software [Article v1.0].Living journal of computational molecular science · 2021Article
- Altered conformational sampling along an evolutionary trajectory changes the catalytic activity of an enzyme.Nature communications · 2020Article
- Combining Experimental Data and Computational Methods for the Non-Computer Specialist.Molecules (Basel, Switzerland) · 2020Review
- Scalable molecular dynamics on CPU and GPU architectures with NAMD.The Journal of chemical physics · 2020Article
- Interpretation of HDX Data by Maximum-Entropy Reweighting of Simulated Structural Ensembles.Biophysical journal · 2020Article
- Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction.Biophysical journal · 2020Article
- Interpretation of spectroscopic data using molecular simulations for the secondary active transporter BetP.The Journal of general physiology · 2019Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Double electron-electron resonance (DEER) is a popular technique that exploits attached spin labels to probe the collective dynamics of biomolecules in a native environment. Like most spectroscopic approaches, DEER detects an ensemble of states accounting for biomolecular dynamics as well as the labels' intrinsic flexibility. Hence, the DEER data alone do not provide high-resolution structural information. To disentangle this variability, we introduce a minimally biased simulation method to sample a structural ensemble that reproduces multiple experimental signals within the uncertainty. In contrast to previous approaches, our method targets the raw data themselves, and thereby it brings forth an unbiased molecular interpretation of the experiments. After validation on the T4 lysozyme, we apply this technique to interpret recent DEER experiments on a membrane transporter binding protein (VcSiaP). The results highlight the large-scale conformational movement that occurs upon substrate binding and reveal that the unbound VcSiaP is more open in solution than the X-ray structure.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.