scholarly journals Spin Saturation Transfer Difference NMR (SSTD NMR): A New Tool to Obtain Kinetic Parameters of Chemical Exchange Processes

10.3791/54499 ◽  
2016 ◽  
Author(s):  
María Teresa Quirós ◽  
Colin Macdonald ◽  
Jesús Angulo ◽  
María Paz Muñoz
Keyword(s):  
Kinetic Parameters ◽  
Chemical Exchange ◽  
Saturation Transfer ◽  
Saturation Transfer Difference ◽  
Exchange Processes

scholarly journals Kinetics of intramolecular chemical exchange by initial growth rates of spin saturation transfer difference experiments (SSTD NMR)

2015 ◽  
Vol 51 (50) ◽  
pp. 10222-10225 ◽  
Author(s):  
M. Teresa Quirós ◽  
Jesús Angulo ◽  
María Paz Muñoz
Keyword(s):  
Kinetic Parameters ◽  
Growth Rates ◽  
Chemical Exchange ◽  
Initial Growth ◽  
Saturation Transfer ◽  
Nmr Method ◽  
Saturation Transfer Difference ◽  
Kinetics Of

Initial growth rates SSTD NMR method is a new powerful tool to obtain the kinetic parameters of intramolecular chemical exchange.

scholarly journals Towards autonomous analysis of Chemical Exchange Saturation Transfer experiments using Deep Neural Networks

2021 ◽  
Author(s):  
Gogulan Karunanithy ◽  
Tairan Yuwen ◽  
Lewis E Kay ◽  
D Flemming Hansen
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Chemical Exchange ◽  
Chemical Shifts ◽  
Conformational Exchange ◽  
Chemical Exchange Saturation Transfer ◽  
Saturation Transfer ◽  
Nmr Data ◽  
Exchange Processes ◽  
Fitting Procedures

Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structure of the conformers that are involved. However, analysis of the NMR data that report on exchanging macromolecules often hinges on complex least-squares fitting procedures as well as human experience and intuition, which, in some cases, limits the widespread use of the methods. The applications of deep neural networks (DNNs) and artificial intelligence have increased significantly in the sciences, and recently, specifically, within the field of biomolecular NMR, where DNNs are now available for tasks such as the reconstruction of sparsely sampled spectra, peak picking, and virtual decoupling. Here we present a DNN for the analysis of chemical exchange saturation transfer (CEST) data reporting on two- or three-site chemical exchange involving sparse state lifetimes of between approximately 3 - 60 ms, the range most frequently observed via experiment. The work presented here focuses on the 1H CEST class of methods that are further complicated, in relation to applications to other nuclei, by anti-phase features. The developed DNNs accurately predict the chemical shifts of nuclei in the exchanging species directly from anti-phase 1HN CEST profiles, along with an uncertainty associated with the predictions. The performance of the DNN was quantitatively assessed using both synthetic and experimental anti-phase CEST profiles. The assessments show that the DNN accurately determines chemical shifts and their associated uncertainties. The DNNs developed here do not contain any parameters for the end-user to adjust and the method therefore allows for autonomous analysis of complex NMR data that report on conformational exchange.

scholarly journals A generalized ratiometric chemical exchange saturation transfer (CEST) MRI approach for mapping renal pH using iopamidol

2017 ◽  
Vol 79 (3) ◽  
pp. 1553-1558 ◽  
Author(s):  
Yin Wu ◽  
Iris Y. Zhou ◽  
Takahiro Igarashi ◽  
Dario L. Longo ◽  
Silvio Aime ◽  
...  
Keyword(s):  
Chemical Exchange ◽  
Chemical Exchange Saturation Transfer ◽  
Saturation Transfer ◽  
Cest Mri
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