4.3 Article

Optimizing frequency sampling in CEST experiments

Journal

JOURNAL OF BIOMOLECULAR NMR
Volume 76, Issue 5-6, Pages 167-183

Publisher

SPRINGER
DOI: 10.1007/s10858-022-00403-2

Keywords

Chemical exchange saturation transfer; Frequency domain sampling; Fourier transform; Protein dynamics; Invisible protein states

Funding

  1. Canadian Institutes of Health Research (CIHR)
  2. Biotechnology and Biological Sciences Research Council UK (BBSRC) [BB/T011831/1]
  3. CIHR [FND-503573]
  4. Natural Sciences and Engineering Council of Canada [2015-04347]

Ask authors/readers for more resources

For the past decade, chemical exchange saturation transfer (CEST) experiments have been successfully used to study exchange processes in biomolecules involving sparsely populated, transiently formed conformers. This study shows that the commonly used lengthy sampling schemes may not be optimal and proposes a reduced frequency sampling approach that does not require a priori knowledge of exchange parameters.
For the past decade chemical exchange saturation transfer (CEST) experiments have been successfully applied to study exchange processes in biomolecules involving sparsely populated, transiently formed conformers. Initial implementations focused on extensive sampling of the CEST frequency domain, requiring significant measurement times. Here we show that the lengthy sampling schemes often used are not optimal and that reduced frequency sampling schedules can be developed without a priori knowledge of the exchange parameters, that only depend on the chosen B-1 field, and, to a lesser extent, on the intrinsic transverse relaxation rates of ground state spins. The reduced sampling approach described here can be used synergistically with other methods for reducing measurement times such as those that excite multiple frequencies in the CEST dimension simultaneously, or make use of non-uniform sampling of indirectly detected time domains, to further decrease measurement times. The proposed approach is validated by analysis of simulated and experimental datasets.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available