ArticleProceedings of the National Academy of Sciences of the United States of America2003
Rapid protein fold determination using unassigned NMR data.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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53 citing papers in PubMed, 125 citations in OpenAlex.
- Recent Advances in NMR Protein Structure Prediction with ROSETTA.International journal of molecular sciences · 2023Review
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Macromolecular modeling and design in Rosetta: recent methods and frameworks.Nature methods · 2020Review
- Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement.Journal of chemical information and modeling · 2020Article
- Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction.Biophysical journal · 2020Article
- Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13.Proteins · 2019Article
- Integrative Protein Modeling in RosettaNMR from Sparse Paramagnetic Restraints.Structure (London, England : 1993) · 2019Article
- Inferring protein 3D structure from deep mutation scans.Nature genetics · 2019Article
- Methods for the Refinement of Protein Structure 3D Models.International journal of molecular sciences · 2019Review
- Article
- CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.BMC bioinformatics · 2018Article
- Automated Fragmentation QM/MM Calculation of NMR Chemical Shifts for Protein-Ligand Complexes.Frontiers in chemistry · 2018Article
- Blind protein structure prediction using accelerated free-energy simulations.Science advances · 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
- AFNMR: automated fragmentation quantum mechanical calculation of NMR chemical shifts for biomolecules.Journal of biomolecular NMR · 2015Article
- NMR data-driven structure determination using NMR-I-TASSER in the CASD-NMR experiment.Journal of biomolecular NMR · 2015Article
- Improved cryoEM-Guided Iterative Molecular Dynamics--Rosetta Protein Structure Refinement Protocol for High Precision Protein Structure Prediction.Journal of chemical theory and computation · 2015Article
- Article
- Computational modeling of membrane proteins.Proteins · 2015Review
- Assessment of CASP10 contact-assisted predictions.Proteins · 2014Article
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2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Experimental structure determination by x-ray crystallography and NMR spectroscopy is slow and time-consuming compared with the rate at which new protein sequences are being identified. NMR spectroscopy has the advantage of rapidly providing the structurally relevant information in the form of unassigned chemical shifts (CSs), intensities of NOESY crosspeaks [nuclear Overhauser effects (NOEs)], and residual dipolar couplings (RDCs), but use of these data are limited by the time and effort needed to assign individual resonances to specific atoms. Here, we develop a method for generating low-resolution protein structures by using unassigned NMR data that relies on the de novo protein structure prediction algorithm, rosetta [Simons, K. T., Kooperberg, C., Huang, E. & Baker, D. (1997) J. Mol. Biol. 268, 209-225] and a Monte Carlo procedure that searches for the assignment of resonances to atoms that produces the best fit of the experimental NMR data to a candidate 3D structure. A large ensemble of models is generated from sequence information alone by using rosetta, an optimal assignment is identified for each model, and the models are then ranked based on their fit with the NMR data assuming the identified assignments. The method was tested on nine protein sequences between 56 and 140 amino acids and published CS, NOE, and RDC data. The procedure yielded models with rms deviations between 3 and 6 A, and, in four of the nine cases, the partial assignments obtained by the method could be used to refine the structures to high resolution (0.6-1.8 A) by repeated cycles of structure generation guided by the partial assignments, followed by reassignment using the newly generated models.
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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.