NMR spectroscopy: a multifaceted approach to macromolecular structure

2000 ◽  
Vol 33 (1) ◽  
pp. 29-65 ◽  
Author(s):  
Ann E. Ferentz ◽  
Gerhard Wagner
Keyword(s):  
Nmr Spectroscopy ◽  
Structure Determination ◽  
Solution Structure ◽  
Residual Dipolar Couplings ◽  
Complete Solution ◽  
Protein Structures ◽  
Sequential Assignment ◽  
Resonance Spectroscopy ◽  
Triple Resonance ◽  
Membrane Bound

1. Introduction 292. Landmarks in NMR of macromolecules 322.1 Protein structures and methods development 322.1.1 Sequential assignment method 322.1.2 Triple-resonance experiments 342.1.3 Structures of large proteins 362.2 Protein–nucleic acid complexes 372.3 RNA structures 382.4 Membrane-bound systems 393. NMR spectroscopy today 403.1 State-of-the-art structure determination 413.2 New methods 443.2.1 Residual dipolar couplings 443.2.2 Direct detection of hydrogen bonds 443.2.3 Spin labeling 453.2.4 Segmental labeling 463.3 Protein complexes 473.4 Mobility studies 503.5 Determination of time-dependent structures 523.6 Drug discovery 534. The future of NMR 544.1 The ease of structure determination 544.2 The ease of making recombinant protein 554.3 Post-translationally modified proteins 554.4 Approaches to large and/or membrane-bound proteins 564.5 NMR in structural genomics 564.6 Synergy of NMR and crystallography in protein structure determination 565. Conclusion 576. Acknowledgements 577. References 57Since the publication of the first complete solution structure of a protein in 1985 (Williamson et al. 1985), tremendous technological advances have brought nuclear magnetic resonance spectroscopy to the forefront of structural biology. Innovations in magnet design, electronics, pulse sequences, data analysis, and computational methods have combined to make NMR an extremely powerful technique for studying biological macromolecules at atomic resolution (Clore & Gronenborn, 1998). Most recently, new labeling and pulse techniques have been developed that push the fundamental line-width limit for resolution in NMR spectroscopy, making it possible to obtain high-field spectra with better resolution than ever before (Dötsch & Wagner, 1998). These methods are facilitating the study of systems of ever-increasing complexity and molecular weight.

scholarly journals REDCRAFT: A computational platform using residual dipolar coupling NMR data for determining structures of perdeuterated proteins in solution

2021 ◽  
Vol 17 (2) ◽  
pp. e1008060
Author(s):  
Casey A. Cole ◽  
Nourhan S. Daigham ◽  
Gaohua Liu ◽  
Gaetano T. Montelione ◽  
Homayoun Valafar
Keyword(s):  
Nmr Spectroscopy ◽  
Structure Determination ◽  
Residual Dipolar Couplings ◽  
Dipolar Coupling ◽  
Nuclear Overhauser Effect ◽  
Critical Role ◽  
Protein Structures ◽  
Perdeuterated Proteins ◽  
Nmr Data

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the three primary experimental means of characterizing macromolecular structures, including protein structures. Structure determination by solution NMR spectroscopy has traditionally relied heavily on distance restraints derived from nuclear Overhauser effect (NOE) measurements. While structure determination of proteins from NOE-based restraints is well understood and broadly used, structure determination from Residual Dipolar Couplings (RDCs) is relatively less well developed. Here, we describe the new features of the protein structure modeling program REDCRAFT and focus on the new Adaptive Decimation (AD) feature. The AD plays a critical role in improving the robustness of REDCRAFT to missing or noisy data, while allowing structure determination of larger proteins from less data. In this report we demonstrate the successful application of REDCRAFT in structure determination of proteins ranging in size from 50 to 145 residues using experimentally collected data, and of larger proteins (145 to 573 residues) using simulated RDC data. In both cases, REDCRAFT uses only RDC data that can be collected from perdeuterated proteins. Finally, we compare the accuracy of structure determination from RDCs alone with traditional NOE-based methods for the structurally novel PF.2048.1 protein. The RDC-based structure of PF.2048.1 exhibited 1.0 Å BB-RMSD with respect to a high-quality NOE-based structure. Although optimal strategies would include using RDC data together with chemical shift, NOE, and other NMR data, these studies provide proof-of-principle for robust structure determination of largely-perdeuterated proteins from RDC data alone using REDCRAFT.

scholarly journals Increased usability, algorithmic improvements and incorporation of data mining for structure calculation of proteins with REDCRAFT software package

2020 ◽  
Vol 21 (S9) ◽  
Author(s):  
Casey Cole ◽  
Caleb Parks ◽  
Julian Rachele ◽  
Homayoun Valafar
Keyword(s):  
Nmr Spectroscopy ◽  
Software Package ◽  
Residual Dipolar Couplings ◽  
Protein Structures ◽  
Primary Source ◽  
Structure Calculation ◽  
Resonance Spectroscopy ◽  
Full Potential ◽  
X Ray ◽  
The Impact

Abstract Background Traditional approaches to elucidation of protein structures by Nuclear Magnetic Resonance spectroscopy (NMR) rely on distance restraints also known as Nuclear Overhauser effects (NOEs). The use of NOEs as the primary source of structure determination by NMR spectroscopy is time consuming and expensive. Residual Dipolar Couplings (RDCs) have become an alternate approach for structure calculation by NMR spectroscopy. In previous works, the software package REDCRAFT has been presented as a means of harnessing the information containing in RDCs for structure calculation of proteins. However, to meet its full potential, several improvements to REDCRAFT must be made. Results In this work, we present improvements to REDCRAFT that include increased usability, better interoperability, and a more robust core algorithm. We have demonstrated the impact of the improved core algorithm in the successful folding of the protein 1A1Z with as high as ±4 Hz of added error. The REDCRAFT computed structure from the highly corrupted data exhibited less than 1.0 Å with respect to the X-ray structure. We have also demonstrated the interoperability of REDCRAFT in a few instances including with PDBMine to reduce the amount of required data in successful folding of proteins to unprecedented levels. Here we have demonstrated the successful folding of the protein 1D3Z (to within 2.4 Å of the X-ray structure) using only N-H RDCs from one alignment medium. Conclusions The additional GUI features of REDCRAFT combined with the NEF compliance have significantly increased the flexibility and usability of this software package. The improvements of the core algorithm have substantially improved the robustness of REDCRAFT in utilizing less experimental data both in quality and quantity.

scholarly journals REDCRAFT: A Computational Platform Using Residual Dipolar Coupling NMR Data for Determining Structures of Perdeuterated Proteins Without NOEs

2020 ◽  
Author(s):  
Casey A. Cole ◽  
Nourhan S. Daigham ◽  
Gaohua Liu ◽  
Gaetano T. Montelione ◽  
Homayoun Valafar
Keyword(s):  
Nmr Spectroscopy ◽  
Structure Determination ◽  
Software Package ◽  
Residual Dipolar Couplings ◽  
Protein Structures ◽  
Dipolar Couplings ◽  
Large Proteins ◽  
Perdeuterated Proteins ◽  
Small Proteins

AbstractNuclear Magnetic Resonance (NMR) spectroscopy is one of the two primary experimental means of characterizing macromolecular structures, including protein structures. Structure determination by NMR spectroscopy has traditionally relied heavily on distance restraints derived from nuclear Overhauser effect (NOE) measurements. While structure determination of proteins from NOE-based restraints is well understood and broadly used, structure determination by NOEs imposes increasing quantity of data for analysis, increased cost of structure determination and is less available in the study of perdeuterated proteins. In the recent decade, Residual Dipolar Couplings (RDCs) have been investigated as an alternative source of data for structural elucidation of proteins by NMR. Several methods have been reported that utilize RDCs in addition to NOEs, and a few utilize RDC data alone. While these methods have individually demonstrated some successes, none of these methods have exposed the full potential of protein structure determination from RDCs. To date, structure determination of proteins from RDCs is limited to small proteins (less than 8.5 kDa) using RDC data from many alignment media (>3) that cannot be collected from larger proteins. Here we present the latest version of the REDCRAFT software package designed for structure determination of proteins from RDC data alone. We have demonstrated the success of REDCRAFT in structure determination of proteins ranging in size from 50 to 145 residues using experimentally collected data and large proteins (145 to 573 residues) using simulated RDC data that can be collected from perdeuterated proteins. Finally, we demonstrate the accuracy of structure determination of REDCRAFT from RDCs alone in application to the structurally novel PF.2048 protein. The RDC-based structure of PF.2048 exhibited 1.0 Å of BB-RMSD with respect to the NOE-based structure by only using a small amount of backbone RDCs (∼3 restraints per residue) compared to what is required by other approaches.Author SummaryResidual Dipolar Couplings have the potential to reduce the cost and the time needed to characterize protein structures. In addition, RDC data have been demonstrated to concurrently elucidate structure of proteins, perform assignment of resonances, and be used in characterization of the internal dynamics of proteins. Given all the advantages associated with the study of proteins from RDC data, based on the statistics provided by the Protein Databank (PDB), surprisingly the only 124 proteins (out of nearly 150,000 proteins) have utilized RDCs as part of their structure determination. Even a smaller subset of these proteins (approximately 7) have utilized RDCs as the primary source of data for structure determination. The impeding factor in the use of RDCs is the challenging computational and analytical aspects of this source of data. In this report, we demonstrate the success of the REDCRAFT software package in structure determination of proteins using RDC data that can be collected from small and large proteins in a routine fashion. REDCRAFT accomplishes the challenging task of structure determination from RDCs by introducing a unique search and optimization technique that is both robust and computationally tractable. Structure determination from routinely collectable RDC data using REDCRAFT can lead to faster and cheaper study of larger and more complex proteins by NMR spectroscopy in solution state.

scholarly journals An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling

2021 ◽  
Vol 8 ◽  
Author(s):  
Kari Gaalswyk ◽  
Zhihong Liu ◽  
Hans J. Vogel ◽  
Justin L. MacCallum
Keyword(s):  
Structure Determination ◽  
Residual Dipolar Couplings ◽  
Chemical Shifts ◽  
Protein Structures ◽  
Physical Modelling ◽  
Paramagnetic Nmr ◽  
Integrative Approach ◽  
Nmr Methods ◽  
Muscle Myosin

Paramagnetic nuclear magnetic resonance (NMR) methods have emerged as powerful tools for structure determination of large, sparsely protonated proteins. However traditional applications face several challenges, including a need for large datasets to offset the sparsity of restraints, the difficulty in accounting for the conformational heterogeneity of the spin-label, and noisy experimental data. Here we propose an integrative approach to structure determination combining sparse paramagnetic NMR with physical modelling to infer approximate protein structural ensembles. We use calmodulin in complex with the smooth muscle myosin light chain kinase peptide as a model system. Despite acquiring data from samples labeled only at the backbone amide positions, we are able to produce an ensemble with an average RMSD of ∼2.8 Å from a reference X-ray crystal structure. Our approach requires only backbone chemical shifts and measurements of the paramagnetic relaxation enhancement and residual dipolar couplings that can be obtained from sparsely labeled samples.

scholarly journals Structure calculation, refinement and validation usingCcpNmr Analysis

2015 ◽  
Vol 71 (1) ◽  
pp. 154-161 ◽  
Author(s):  
Simon P. Skinner ◽  
Benjamin T. Goult ◽  
Rasmus H. Fogh ◽  
Wayne Boucher ◽  
Tim J. Stevens ◽  
...  
Keyword(s):  
Structure Determination ◽  
Solution Structure ◽  
Residual Dipolar Couplings ◽  
Structure Calculation ◽  
Biological Macromolecules ◽  
Nmr Structure Determination ◽  
Determination Process ◽  
The Many ◽  
Nmr Restraints

CcpNmr Analysisprovides a streamlined pipeline for both NMR chemical shift assignment and structure determination of biological macromolecules. In addition, it encompasses tools to analyse the many additional experiments that make NMR such a pivotal technique for research into complex biological questions. This report describes howCcpNmr Analysiscan seamlessly link together all of the tasks in the NMR structure-determination process. It details each of the stages from generating NMR restraints [distance, dihedral, hydrogen bonds and residual dipolar couplings (RDCs)], exporting these to and subsequently re-importing them from structure-calculation software (such as the programsCYANAorARIA) and analysing and validating the results obtained from the structure calculation to, ultimately, the streamlined deposition of the completed assignments and the refined ensemble of structures into the PDBe repository. Until recently, such solution-structure determination by NMR has been quite a laborious task, requiring multiple stages and programs. However, with the new enhancements toCcpNmr Analysisdescribed here, this process is now much more intuitive and efficient and less error-prone.

scholarly journals Solid-State Protein-Structure Determination with Proton-Detected Triple-Resonance 3D Magic-Angle-Spinning NMR Spectroscopy

2007 ◽  
Vol 46 (44) ◽  
pp. 8380-8383 ◽  
Author(s):  
Donghua H. Zhou ◽  
John J. Shea ◽  
Andrew J. Nieuwkoop ◽  
W. Trent Franks ◽  
Benjamin J. Wylie ◽  
...  
Keyword(s):  
Protein Structure ◽  
Solid State ◽  
Nmr Spectroscopy ◽  
Structure Determination ◽  
Protein Structure Determination ◽  
Magic Angle Spinning ◽  
Magic Angle ◽  
Triple Resonance ◽  
Angle Spinning

scholarly journals Structure Determination by Single-Particle Cryo-Electron Microscopy: Only the Sky (and Intrinsic Disorder) is the Limit

2019 ◽  
Vol 20 (17) ◽  
pp. 4186 ◽  
Author(s):  
Emeka Nwanochie ◽  
Vladimir N. Uversky
Keyword(s):  
Electron Microscopy ◽  
Nmr Spectroscopy ◽  
Structure Determination ◽  
Single Particle ◽  
Protein Structures ◽  
X Ray ◽  
X Ray Crystallography ◽  
Intrinsically Disordered ◽  
Small Proteins ◽  
Cryo Electron Microscopy

Traditionally, X-ray crystallography and NMR spectroscopy represent major workhorses of structural biologists, with the lion share of protein structures reported in protein data bank (PDB) being generated by these powerful techniques. Despite their wide utilization in protein structure determination, these two techniques have logical limitations, with X-ray crystallography being unsuitable for the analysis of highly dynamic structures and with NMR spectroscopy being restricted to the analysis of relatively small proteins. In recent years, we have witnessed an explosive development of the techniques based on Cryo-electron microscopy (Cryo-EM) for structural characterization of biological molecules. In fact, single-particle Cryo-EM is a special niche as it is a technique of choice for the structural analysis of large, structurally heterogeneous, and dynamic complexes. Here, sub-nanometer atomic resolution can be achieved (i.e., resolution below 10 Å) via single-particle imaging of non-crystalline specimens, with accurate 3D reconstruction being generated based on the computational averaging of multiple 2D projection images of the same particle that was frozen rapidly in solution. We provide here a brief overview of single-particle Cryo-EM and show how Cryo-EM has revolutionized structural investigations of membrane proteins. We also show that the presence of intrinsically disordered or flexible regions in a target protein represents one of the major limitations of this promising technique.

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