scholarly journals Rapid Structure Determination of Molecular Solids Using Chemical Shifts Directed by Unambiguous Prior Constraints

2019 ◽  
Vol 141 (42) ◽  
pp. 16624-16634 ◽  
Author(s):  
Albert Hofstetter ◽  
Martins Balodis ◽  
Federico M. Paruzzo ◽  
Cory M. Widdifield ◽  
Gabriele Stevanato ◽  
...  
2013 ◽  
Vol 117 (23) ◽  
pp. 12258-12265 ◽  
Author(s):  
Dmytro V. Dudenko ◽  
P. Andrew Williams ◽  
Colan E. Hughes ◽  
Oleg N. Antzutkin ◽  
Sitaram P. Velaga ◽  
...  

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.


2014 ◽  
Vol 70 (a1) ◽  
pp. C1557-C1557
Author(s):  
Kenneth Harris

Structure determination of organic molecular solids from powder X-ray diffraction (XRD) data [1] is nowadays carried out extensively by researchers in both academia and industry, and the development of new methodology in this field has made particularly significant impact in the pharmaceuticals industry within the last 20 years or so. However, although software for carrying out each stage of the procedure for structure determination from powder XRD data is now readily accessible and relatively straightforward to use, it is essential that the results from such structure determination calculations are subjected to careful scrutiny to confirm that the final structure obtained is actually correct. In this regard, it can be particularly advantageous to augment the analysis of the powder XRD data and to assist the scrutiny of the structural results by considering complementary structural information derived from other experimental and computational techniques. Techniques that can be particularly valuable in this regard include solid-state NMR spectroscopy, energy calculations (either on individual molecules or periodic crystal structures), vibrational spectroscopies, and techniques of thermal analysis (e.g. DSC and TGA). The lecture will give an overview of the current "state of the art" in the structure determination of organic materials from powder XRD data, giving emphasis [2,3] to the opportunities to enhance the structure determination process by making use of information derived from other experimental (especially solid-state NMR) and computational techniques. Recent results will be presented, with emphasis on raising issues of relevance to research on pharmaceutical materials.


2008 ◽  
Vol 2008 (27) ◽  
pp. 4640-4646 ◽  
Author(s):  
Shamil Latypov ◽  
Alsu Balandina ◽  
Marco Boccalini ◽  
Alessandra Matteucci ◽  
Konstantin Usachev ◽  
...  

2019 ◽  
Vol 218 ◽  
pp. 191-201 ◽  
Author(s):  
Justinas Sakas ◽  
Nicholle G. A. Bell

A suite of NMR experiments using combined chemical shifts to separate resonances in two rather than three dimensions.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Manuel Cordova ◽  
Martins Balodis ◽  
Albert Hofstetter ◽  
Federico Paruzzo ◽  
Sten O. Nilsson Lill ◽  
...  

AbstractKnowledge of the structure of amorphous solids can direct, for example, the optimization of pharmaceutical formulations, but atomic-level structure determination in amorphous molecular solids has so far not been possible. Solid-state nuclear magnetic resonance (NMR) is among the most popular methods to characterize amorphous materials, and molecular dynamics (MD) simulations can help describe the structure of disordered materials. However, directly relating MD to NMR experiments in molecular solids has been out of reach until now because of the large size of these simulations. Here, using a machine learning model of chemical shifts, we determine the atomic-level structure of the hydrated amorphous drug AZD5718 by combining dynamic nuclear polarization-enhanced solid-state NMR experiments with predicted chemical shifts for MD simulations of large systems. From these amorphous structures we then identify H-bonding motifs and relate them to local intermolecular complex formation energies.


2010 ◽  
pp. n/a-n/a ◽  
Author(s):  
Stefano Chimichi ◽  
Marco Boccalini ◽  
Alessandra Matteucci ◽  
Sergey V. Kharlamov ◽  
Shamil K. Latypov ◽  
...  

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