A Proton‐Detected 4D Solid‐State NMR Experiment for Protein Structure Determination

Huber, Matthias; Hiller, Sebastian; Schanda, Paul; Ernst, Matthias; Böckmann, Anja; Verel, René; Meier, Beat H.

doi:10.1002/cphc.201100062

Cited by 166 publications

(175 citation statements)

References 57 publications

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confidence: 99%

“…These are based on MAS solidstate NMR experiments, [5][6][7][8][9][10][11] and cryo-electron microscopic image reconstructions. 12 Even though there is some controversy concerning the conformational space that Ab fibrils can adopt, all published models, including the 2-fold 7,10 and 3-fold 9 symmetric Ab 1-40 fibril structure suggested by Tycko, and Bertini and co-workers, agree on the basic building block which involves a b-sheet (b1, residues 12-24), a turn, and a second b-sheet (b2, residues [28][29][30][31][32][33][34][35][36][37][38][39][40]. Biophysical studies indicate a certain degree of conformational plasticity for the N-terminal b-sheet.…”

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confidence: 99%

“…[26][27][28][29] Fibril samples prepared from deuterated Ab peptides allow us to collect long range distance restraints which will help to refine the quarternary structure of the fibril. 30,31 In the long run, this labeling scheme will allow an artifact-free quantification of dynamics in the solid-state without spin diffusion as a potential source of error. 21,32 The registry of monomers which are concatenated in the amyloid fibril via backbone hydrogen bonds is restrained employing backbone-backbone correlations from XHHY (X, Y = 13 C or 15 N) type experiments.…”

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Hydrogen bonding involving side chain exchangeable groups stabilizes amyloid quarternary structure

Agarwal

Linser

Dasari

et al. 2013

Phys. Chem. Chem. Phys.

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The amyloid b-peptide (Ab) is the major structural component of amyloid fibrils in the plaques of brains of Alzheimer's disease patients. Numerous studies have addressed important aspects of secondary and tertiary structure of fibrils. In electron microscopic images, fibrils often bundle together. The mechanisms which drive the association of protofilaments into bundles of fibrils are not known. We show here that amino acid side chain exchangeable groups like e.g. histidines can provide useful restraints to determine the quarternary assembly of an amyloid fibril. Exchangeable protons are only observable if a side chain hydrogen bond is formed and the respective protons are protected from exchange. The method relies on deuteration of the Ab peptide. Exchangeable deuterons are substituted with protons, before fibril formation is initiated.Alzheimer's disease (AD) is a slowly progressive neurological disorder which is associated with memory loss, cognitive impairment and finally dementia and death. The amyloid b-peptide (Ab) is the major structural component of amyloid fibrils in the plaques of brains of Alzheimer's disease patients. Ab is a cleavage product resulting from Alzheimer Precursor Protein (APP) processing. 1 The g-secretase cut yields Ab fragments of different lengths of which Ab40 and Ab42 are most abundant. 2,3 In vitro, the Ab peptide aggregates over time into oligomers and fibrillar structures. 4 In the past, several Ab fibril structure models have been suggested. These are based on MAS solidstate NMR experiments, 5-11 and cryo-electron microscopic image reconstructions. 12 Even though there is some controversy concerning the conformational space that Ab fibrils can adopt, all published models, including the 2-fold 7,10 and 3-fold 9 symmetric Ab 1-40 fibril structure suggested by Tycko, and Bertini and co-workers, agree on the basic building block which involves a b-sheet (b1, residues 12-24), a turn, and a second b-sheet (b2, residues 28-40). Biophysical studies indicate a certain degree of conformational plasticity for the N-terminal b-sheet. 13,14 Whereas b2 is present in all the studies, b1 can be truncated or does not adopt a regular b-sheet structure. Depending on the preparation conditions, amide protons in the region of the peptide where the first b-strand is expected show differential H/D protection factors. 13 Similarly, a certain degree of conformational variability in the N-terminus is suggested using cryo-electron microscopy. 14 In all structural models, Ab peptides are arranged in a parallel fashion. An antiparallel arrangement is only observed for the Iowa mutant Ab-D23N, 15 and for truncated forms of the peptide such as Ab [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] . 16 The fibril structure is stabilized in particular by hydrogen bonding interactions. Therefore, observation of exchangeable and titratable groups is of particular interest to identify hydrogen bonding patterns. We and others could show in the past that high resolution proton spectra can be obtained for...

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Hydrogen bonding involving side chain exchangeable groups stabilizes amyloid quarternary structure

Agarwal

Linser

Dasari

et al. 2013

Phys. Chem. Chem. Phys.

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“…Previously, Huber et al (25) made two tests. They produced an ensemble of 200 structures using CYANA (26) coupled with assumed backbone ϕ=ψ angles [predicted from NMR chemical shifts using Talos+ (27)] and the measured ILV-methyl interactions.…”

Section: Resultsmentioning

confidence: 99%

Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference

MacCallum

Pérez

Dill

2015

Proc. Natl. Acad. Sci. U.S.A.

145

233

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More than 100,000 protein structures are now known at atomic detail. However, far more are not yet known, particularly among large or complex proteins. Often, experimental information is only semireliable because it is uncertain, limited, or confusing in important ways. Some experiments give sparse information, some give ambiguous or nonspecific information, and others give uncertain information-where some is right, some is wrong, but we don't know which. We describe a method called Modeling Employing Limited Data (MELD) that can harness such problematic information in a physics-based, Bayesian framework for improved structure determination. We apply MELD to eight proteins of known structure for which such problematic structural data are available, including a sparse NMR dataset, two ambiguous EPR datasets, and four uncertain datasets taken from sequence evolution data. MELD gives excellent structures, indicating its promise for experimental biomolecule structure determination where only semireliable data are available.protein structure | molecular modeling | integrative structural biology | Bayesian inference I ncreasingly, structures are determined using integrative structural biology approaches, where direct experimental data are combined with computer-based models (1). Important successes in integrative structural biology have come from pioneering methods such as Modeler (2, 3), methods based on Rosetta (4-7), and others (8). Atomistic molecular dynamics (MD) simulations can be a powerful tool in integrative structural biology, because they capture physical principles and thermodynamic forcesinformation that is otherwise orthogonal to purely structural observations. However, there remain many situations in which it is not yet possible to properly integrate external knowledge with atomistic MD to infer biomolecular structures. Often, the external knowledge is challenging in one or more of the following ways. (i) Sparse data provide too little information to fully constrain the structure. (ii) Ambiguous data are not very specific, allowing alternative structural interpretations. (iii) Uncertain data cannot be interpreted at face value, because they contain false-positive signals that can be misdirective. Determining new challenging protein structures requires ways to handle semireliable data.Here, we describe a physics-based, Bayesian computational method called MELD (Modeling Employing Limited Data). It is a procedure for making rigorous inferences from limited or uncertain data. We build upon previous Bayesian approaches (9-14), which share the key feature of combining prior belief with the available data to produce statistically consistent samples from a posterior distribution, rather than searching for a single well-scoring model. The key properties of MELD are the rigorous treatment of statistical mechanics, a novel likelihood function that can handle uncertain data, and a graphics processing unit (GPU)-accelerated sampling strategy that makes the calculations tractable.MELD uses free energy as the princi...

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“…[45][46][47][48][49] Because of this reason and due to the enhanced signal-to-noise ratio rendered by proton detection, the development of protonbased solid-state NMR techniques has been the main focus of recent ultrafast-MAS studies. [50][51][52][53][54][55][56][57][58][59][60] Recent studies from our laboratory have demonstrated the feasibility of recoupling proton-proton dipolar couplings, 14,[61][62][63] protonbased multidimensional experiments, [64][65][66][67] spectral-editing techniques, 68,69 and proton-proton distance measurements 69 under ultrafast-MAS conditions, whereas effective use of deuteration has also very recently been shown to be useful in proton-proton distance measurements by Reif et al 70,71 We have also shown the role of dipolar couplings that control the efficiency of refocused-INEPT pulse sequence under ultrafast-MAS. 72 While the recent proton-based ultrafast-MAS studies have successfully demonstrated the feasibility of using wellresolved proton chemical shift resonances, there is a need for methods to assign proton resonances.…”

Section: Introductionmentioning

confidence: 99%

Constant-time 2D and 3D through-bond correlation NMR spectroscopy of solids under 60 kHz MAS

Zhang

Ramamoorthy

2016

The Journal of Chemical Physics

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Establishing connectivity and proximity of nuclei is an important step in elucidating the structure and dynamics of molecules in solids using magic angle spinning (MAS) NMR spectroscopy. Although recent studies have successfully demonstrated the feasibility of proton-detected multidimensional solid-state NMR experiments under ultrafast-MAS frequencies and obtaining high-resolution spectral lines of protons, assignment of proton resonances is a major challenge. In this study, we first re-visit and demonstrate the feasibility of 2D constant-time uniform-sign cross-peak correlation (CTUC-COSY) NMR experiment on rigid solids under ultrafast-MAS conditions, where the sensitivity of the experiment is enhanced by the reduced spin-spin relaxation rate and the use of low radio-frequency power for heteronuclear decoupling during the evolution intervals of the pulse sequence. In addition, we experimentally demonstrate the performance of a proton-detected pulse sequence to obtain a 3D 1 H/ 13 C/ 1 H chemical shift correlation spectrum by incorporating an additional cross-polarization period in the CTUC-COSY pulse sequence to enable proton chemical shift evolution and proton detection in the incrementable t 1 and t 3 periods, respectively. In addition to through-space and through-bond 13 C/ 1 H and 13 C/ 13 C chemical shift correlations, the 3D 1 H/ 13 C/ 1 H experiment also provides a COSY-type 1 H/ 1 H chemical shift correlation spectrum, where only the chemical shifts of those protons, which are bonded to two neighboring carbons, are correlated. By extracting 2D F1/F3 slices ( 1 H/ 1 H chemical shift correlation spectrum) at different 13 C chemical shift frequencies from the 3D 1 H/ 13 C/ 1 H spectrum, resonances of proton atoms located close to a specific carbon atom can be identified. Overall, the through-bond and through-space homonuclear/heteronuclear proximities determined from the 3D 1 H/ 13 C/ 1 H experiment would be useful to study the structure and dynamics of a variety of chemical and biological solids. C 2016 AIP Publishing LLC. [http://dx

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A Proton‐Detected 4D Solid‐State NMR Experiment for Protein Structure Determination

Cited by 166 publications

References 57 publications

Hydrogen bonding involving side chain exchangeable groups stabilizes amyloid quarternary structure

Hydrogen bonding involving side chain exchangeable groups stabilizes amyloid quarternary structure

Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference

Constant-time 2D and 3D through-bond correlation NMR spectroscopy of solids under 60 kHz MAS

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