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Development of new approaches to NMR...

Coggins, Brian E.

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Development of new approaches to NMR data collection for protein structure determination.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Development of new approaches to NMR data collection for protein structure determination./
作者:	Coggins, Brian E.
面頁冊數:	231 p.
附註:	Adviser: Pei Zhou.
Contained By:	Dissertation Abstracts International68-03B.
標題:	Biophysics, General. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3255592

Development of new approaches to NMR data collection for protein structure determination.
Coggins, Brian E.

Development of new approaches to NMR data collection for protein structure determination. - 231 p.

Adviser: Pei Zhou.

Thesis (Ph.D.)--Duke University, 2007.

Multidimensional nuclear magnetic resonance (NMR) spectroscopy has become one of the most important techniques available for studying the structure and function of biological macromolecules at atomic resolution. The conventional approach to multidimensional NMR involves the sampling of the time domain on a Cartesian grid followed by a multidimensional Fourier transform (FT). While this approach yields high quality spectra, as the number of dimensions is increased the time needed for sampling on a Cartesian grid increases exponentially, making it impractical to record 4-D spectra at high resolution and impossible to record 5-D spectra at all.Subjects--Topical Terms:

1019105
Biophysics, General.

Development of new approaches to NMR data collection for protein structure determination.
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245 1 0 $a Development of new approaches to NMR data collection for protein structure determination.
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502 $a Thesis (Ph.D.)--Duke University, 2007.
520 $a Multidimensional nuclear magnetic resonance (NMR) spectroscopy has become one of the most important techniques available for studying the structure and function of biological macromolecules at atomic resolution. The conventional approach to multidimensional NMR involves the sampling of the time domain on a Cartesian grid followed by a multidimensional Fourier transform (FT). While this approach yields high quality spectra, as the number of dimensions is increased the time needed for sampling on a Cartesian grid increases exponentially, making it impractical to record 4-D spectra at high resolution and impossible to record 5-D spectra at all.
520 $a This thesis describes new approaches to data collection and processing that make it possible to obtain spectra at higher resolution and/or with a higher dimensionality than was previously feasible with the conventional method. The central focus of this work has been the sampling of the time domain along radial spokes, which was recently introduced into the NMR community. If each radial spoke is processed by an FT with respect to radius, a set of projections of the higher-dimensional spectrum are obtained. Full spectra at high resolution can be generated from these projections via tomographic reconstruction. We generalized the lower-value reconstruction algorithm from the literature, and later integrated it with the backprojection algorithm in a hybrid reconstruction method. These methods permit the reconstruction of accurate 4-D and 5-D spectra at very high resolution, from only a small number of projections, as we demonstrated in the reconstruction of 4-D and 5-D sequential assignment spectra on small and large proteins. For nuclear Overhauser spectroscopy (NOESY), used to measure interproton distances in proteins, one requires quantitative reconstructions. We have successfully obtained these using filtered backprojection, which we found was equivalent to processing the radially sampled data by a polar FT. All of these methods represent significant gains in data collection efficiency over conventional approaches.
520 $a The polar FT interpretation suggested that the problem could be analyzed using FT theory, to design even more efficient methods. We have developed a new approach to sampling, using concentric rings of sampling points, which represents a further improvement in efficiency and sensitivity over radial sampling.
590 $a School code: 0066.
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