ArticleJournal of the American Chemical Society2010
Accurate automated protein NMR structure determination using unassigned NOESY data.
Article in Journal of the American Chemical Society, 2010. 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.
- AlphaFold Models of Small Proteins Rival the Accuracy of Solution NMR Structures.Frontiers in molecular biosciences · 2022Article
- Simultaneous Assignment and Structure Determination of Proteins From Sparsely Labeled NMR Datasets.Frontiers in molecular biosciences · 2021Article
- Blind protein structure prediction using accelerated free-energy simulations.Science advances · 2016Article
- Guiding automated NMR structure determination using a global optimization metric, the NMR DP score.Journal of biomolecular NMR · 2015Article
- Robust and highly accurate automatic NOESY assignment and structure determination with Rosetta.Journal of biomolecular NMR · 2014Article
- Automatic NOESY assignment in CS-RASREC-Rosetta.Journal of biomolecular NMR · 2014Article
- Solution structure and DNA-binding properties of the winged helix domain of the meiotic recombination HOP2 protein.The Journal of biological chemistry · 2014Article
- Protein NMR structures refined with Rosetta have higher accuracy relative to corresponding X-ray crystal structures.Journal of the American Chemical Society · 2014Article
- Assessment of CASP10 contact-assisted predictions.Proteins · 2014Article
- Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker.Journal of biomolecular NMR · 2013Article
- Improving 3D structure prediction from chemical shift data.Journal of biomolecular NMR · 2013Article
- Resolution-by-proxy: a simple measure for assessing and comparing the overall quality of NMR protein structures.Journal of biomolecular NMR · 2012Article
- RPF: a quality assessment tool for protein NMR structures.Nucleic acids research · 2012Article
- Blind testing of routine, fully automated determination of protein structures from NMR data.Structure (London, England : 1993) · 2012Article
- Protein structure validation by generalized linear model root-mean-square deviation prediction.Protein science : a publication of the Protein Society · 2012Article
- The Protein Structure Initiative: achievements and visions for the future.F1000 biology reports · 2012Article
- Synergistic applications of MD and NMR for the study of biological systems.Journal of biomedicine & biotechnology · 2012Review
- A Bayesian approach for determining protein side-chain rotamer conformations using unassigned NOE data.Journal of computational biology : a journal of computational molecular cell biology · 2011Article
- Structure of the BamC two-domain protein obtained by Rosetta with a limited NMR data set.Journal of molecular biology · 2011Article
- Determination of the structures of symmetric protein oligomers from NMR chemical shifts and residual dipolar couplings.Journal of the American Chemical Society · 2011Article
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8 authors.
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Abstract
Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.
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