A fast approach to 3D HSQC-based spectroscopy based on a Fourier phase encoding of pre-targeted resonances
Autor: | Lucio Frydman, Yulan Lin, Zhiyong Zhang, Pieter E. S. Smith |
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Rok vydání: | 2017 |
Předmět: |
Nuclear and High Energy Physics
Speedup 010405 organic chemistry Chemistry Biophysics 010402 general chemistry Condensed Matter Physics 01 natural sciences Biochemistry Spectral line 0104 chemical sciences symbols.namesake Fourier transform Nuclear magnetic resonance Heteronuclear molecule symbols Spectroscopy Algorithm Heteronuclear single quantum coherence spectroscopy Coherence (physics) Curse of dimensionality |
Zdroj: | Journal of Magnetic Resonance. 274:95-102 |
ISSN: | 1090-7807 |
DOI: | 10.1016/j.jmr.2016.11.011 |
Popis: | Multidimensional Nuclear Magnetic Resonance (NMR) provides a unique window into structure and dynamics at an atomic level. Traditionally, given the scan-by-scan time modulation involved in these experiments, the duration of nD NMR increases exponentially with spectral dimensionality. In addition, acquisition times increase as the number of spectral elements being sought in each indirect domain – given by the ratio between the spectral bandwidth being targeted and the resolution desired. These long sampling times can be substantially reduced by exploiting information that is often available from lower-dimensionality acquisitions. This work presents a novel approach that exploits previous 2D information to speed up the acquisition of 3D spectra, based on what we denote as a Time-Optimized FouriEr Encoding (TOFEE) of pre-targeted peaks. Such 3D TOFEE experiments, which present points in common with Hadamard-encoded 3D acquisitions, do not necessarily require more scans than their 2D counterparts. This is here demonstrated based on extensions of 2D Heteronuclear Single-quantum Coherence (HSQC) experiments, to 3D HSQC-TOCSY or 3D HSQC-NOESY acquisitions. The theoretical basis of this new approach is given, and experimental demonstrations are presented on small molecule and protein-based model systems. |
Databáze: | OpenAIRE |
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