paramagnetic nmr
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2022 ◽  
Author(s):  
Valeria Gabrielli ◽  
Roberto Baretta ◽  
Roberto Pilot ◽  
Alberta Ferrarini ◽  
Marco Frasconi

2022 ◽  
Vol 134 (3) ◽  
Author(s):  
Dmitry Yu. Aleshin ◽  
Rosa Diego ◽  
Leoní A. Barrios ◽  
Yulia V. Nelyubina ◽  
Guillem Aromí ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Danhua Dai ◽  
Xianwei Wang ◽  
Yiwei Liu ◽  
Xiao-Liang Yang ◽  
Clemens Glaubitz ◽  
...  

AbstractNuclear magnetic resonance (NMR) spectroscopy is a powerful and popular technique for probing the molecular structures, dynamics and chemical properties. However the conventional NMR spectroscopy is bottlenecked by its low sensitivity. Dynamic nuclear polarization (DNP) boosts NMR sensitivity by orders of magnitude and resolves this limitation. In liquid-state this revolutionizing technique has been restricted to a few specific non-biological model molecules in organic solvents. Here we show that the carbon polarization in small biological molecules, including carbohydrates and amino acids, can be enhanced sizably by in situ Overhauser DNP (ODNP) in water at room temperature and at high magnetic field. An observed connection between ODNP 13C enhancement factor and paramagnetic 13C NMR shift has led to the exploration of biologically relevant heterocyclic compound indole. The QM/MM MD simulation underscores the dynamics of intermolecular hydrogen bonds as the driving force for the scalar ODNP in a long-living radical-substrate complex. Our work reconciles results obtained by DNP spectroscopy, paramagnetic NMR and computational chemistry and provides new mechanistic insights into the high-field scalar ODNP.


2021 ◽  
Vol 8 ◽  
Author(s):  
Kari Gaalswyk ◽  
Zhihong Liu ◽  
Hans J. Vogel ◽  
Justin L. MacCallum

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.


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