ArticleMolecular & cellular proteomics : MCP2014
Determining protein complex structures based on a Bayesian model of in vivo Förster resonance energy transfer (FRET) data.
Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Tutorial on integrative spatiotemporal modeling by integrative modeling platform.Protein science : a publication of the Protein Society · 2025Article
- CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2.Nature methods · 2024Article
- Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy.Biochemistry · 2023Article
- Predicting structures of large protein assemblies using combinatorial assembly algorithm and AlphaFold2.bioRxiv : the preprint server for biology · 2023Article
- Prediction of Protein Complex Structure Using Surface-Induced Dissociation and Cryo-Electron Microscopy.Analytical chemistry · 2021Article
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Computational structure modeling for diverse categories of macromolecular interactions.Current opinion in structural biology · 2020Review
- SSEThread: Integrative threading of the DNA-PKcs sequence based on data from chemical cross-linking and hydrogen deuterium exchange.Progress in biophysics and molecular biology · 2019Article
- Archiving and disseminating integrative structure models.Journal of biomolecular NMR · 2019Article
- Analysis of the protein composition of the spindle pole body during sporulation in Ashbya gossypii.PloS one · 2019Article
- Modeling Protein Complexes Using Restraints from Crosslinking Mass Spectrometry.Structure (London, England : 1993) · 2018Article
- Integrative structure modeling with the Integrative Modeling Platform.Protein science : a publication of the Protein Society · 2018Article
- The molecular architecture of the yeast spindle pole body core determined by Bayesian integrative modeling.Molecular biology of the cell · 2017Article
- TOWARD BAYESIAN INFERENCE OF THE SPATIAL DISTRIBUTION OF PROTEINS FROM THREE-CUBE FÖRSTER RESONANCE ENERGY TRANSFER DATA.The annals of applied statistics · 2017Article
- Determining Atomistic SAXS Models of Tri-Ubiquitin Chains from Bayesian Analysis of Accelerated Molecular Dynamics Simulations.Journal of chemical theory and computation · 2017Article
- A Residue-Resolved Bayesian Approach to Quantitative Interpretation of Hydrogen-Deuterium Exchange from Mass Spectrometry: Application to Characterizing Protein-Ligand Interactions.The journal of physical chemistry. B · 2017Article
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- Metadynamic metainference: Enhanced sampling of the metainference ensemble using metadynamics.Scientific reports · 2016Article
- Assessment of the utility of contact-based restraints in accelerating the prediction of protein structure using molecular dynamics simulations.Protein science : a publication of the Protein Society · 2016Article
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11 authors.
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Abstract
The use of in vivo Förster resonance energy transfer (FRET) data to determine the molecular architecture of a protein complex in living cells is challenging due to data sparseness, sample heterogeneity, signal contributions from multiple donors and acceptors, unequal fluorophore brightness, photobleaching, flexibility of the linker connecting the fluorophore to the tagged protein, and spectral cross-talk. We addressed these challenges by using a Bayesian approach that produces the posterior probability of a model, given the input data. The posterior probability is defined as a function of the dependence of our FRET metric FRETR on a structure (forward model), a model of noise in the data, as well as prior information about the structure, relative populations of distinct states in the sample, forward model parameters, and data noise. The forward model was validated against kinetic Monte Carlo simulations and in vivo experimental data collected on nine systems of known structure. In addition, our Bayesian approach was validated by a benchmark of 16 protein complexes of known structure. Given the structures of each subunit of the complexes, models were computed from synthetic FRETR data with a distance root-mean-squared deviation error of 14 to 17 Å. The approach is implemented in the open-source Integrative Modeling Platform, allowing us to determine macromolecular structures through a combination of in vivo FRETR data and data from other sources, such as electron microscopy and chemical cross-linking.
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