The introduction of AlphaFold has fundamentally changed our ability to predict the structure of proteins from their primary sequence of amino acids. As machine learning (ML) and artificial intelligence (AI) based protein prediction continues to advance, we examine the potential of hybrid techniques that combine experiment and computation that may yield more accurate structures than AI alone with significantly reduced experimental burden. We have developed heuristics comparing N-edited NOESY...
[NMR paper] Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank
Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank
Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide...
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nmrlearner
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03-24-2024 06:32 AM
Optimization and validation of multi-state NMR protein structures using structural correlations
Optimization and validation of multi-state NMR protein structures using structural correlations
Abstract
Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints...
nmrlearner
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03-21-2022 04:01 AM
[NMR paper] Optimization and validation of multi-state NMR protein structures using structural correlations
Optimization and validation of multi-state NMR protein structures using structural correlations
Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify......
nmrlearner
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03-21-2022 04:01 AM
[NMR paper] Assessment of Prediction Methods for Protein Structures Determined by NMR in CASP14: Impact of AlphaFold2
Assessment of Prediction Methods for Protein Structures Determined by NMR in CASP14: Impact of AlphaFold2
NMR studies can provide unique information about protein conformations in solution. In CASP14, three reference structures provided by solution NMR methods were available (T1027, T1029, and T1055), as well as a fourth data set of NMR-derived contacts for an integral membrane protein (T1088). For the three targets with NMR-based structures, the best prediction results ranged from very good (GDT_TS = 0.90, for T1055) to poor (GDT_TS = 0.47, for T1029). We explored the basis of these...
nmrlearner
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09-25-2021 02:17 PM
[NMR paper] NMR hawk-eyed view of AlphaFold2 structures
NMR hawk-eyed view of AlphaFold2 structures
The prediction of the three-dimensional structure of proteins from the amino acid sequence made a stunning breakthrough reaching atomic accuracy. Using the neural network-based method AlphaFold2 three-dimensional structures of almost the entire human proteome have been predicted and made available (https://www.alphafold.ebi.ac.uk). To gain insight into how well AlphaFold2 structures represent the conformation of proteins in solution, I here compare the AlphaFold2 structures of selected small...
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nmrlearner
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09-03-2021 02:54 AM
NMR hawk-eyed view of AlphaFold2 structures
NMR hawk-eyed view of AlphaFold2 structures
Abstract
The prediction of the three-dimensional structure of proteins from the amino acid sequence made a stunning breakthrough reaching atomic accuracy. Using the neural network-based method AlphaFold2 three-dimensional structures of almost the entire human proteome have been predicted and made available (https://www.alphafold.ebi.ac.uk). To gain insight into how well AlphaFold2 structures represent the conformation of proteins in solution, I here compare the AlphaFold2 structures of selected small proteins with their 3D structures that were...
nmrlearner
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09-02-2021 02:00 AM
[NMR paper] An overview of tools for the validation of protein NMR structures.
An overview of tools for the validation of protein NMR structures.
An overview of tools for the validation of protein NMR structures.
J Biomol NMR. 2013 Jul 23;
Authors: Vuister GW, Fogh RH, Hendrickx PM, Doreleijers JF, Gutmanas A
Abstract
Biomolecular structures at atomic resolution present a valuable resource for the understanding of biology. NMR spectroscopy accounts for 11*% of all structures in the PDB repository. In response to serious problems with the accuracy of some of the NMR-derived structures and in order to facilitate...
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07-24-2013 04:52 PM
Validation of NMR-derived protein structures, Chris Spronk
Here's a good PowerPoint presentation by Chris Spronk (University of Nijmegen, The Netherlands) on the subject of validating NMR protein structure results (adapted by Jurgen F. Doreleijers - University of Wisconsin, Madison, USA)
http://tang.bmrb.wisc.edu/~jurgen/presents/Madison/Biochem%20801/NMR_validation_biochem801_2005.ppt
The presentation is very well-annotated, so be sure to adjust your view in PowerPoint so that you can see the notes.
NMR Spectroscopy for the Validation of AlphaFold2 Structures
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