A Slice-based ^C-detected NMR Spin System Forming and Resonance Assignment Method

Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently, <inline-formula><tex-math notation="LaTeX">^1</tex-math> <inline-graphic xlink:href="alazmi-ieq2-2849728.gif"/> <...

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Vydáno v:IEEE/ACM transactions on computational biology and bioinformatics Ročník 15; číslo 6; s. 1999 - 2008
Hlavní autoři: Alazmi, Meshari, Abbas, Ahmed, Guo, Xianrong, Fan, Ming, Li, Lihua, Gao, Xin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1545-5963, 1557-9964
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Abstract Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently, <inline-formula><tex-math notation="LaTeX">^1</tex-math> <inline-graphic xlink:href="alazmi-ieq2-2849728.gif"/> </inline-formula>H-detected experiments are the dominant NMR technique used due to the high sensitivity of <inline-formula><tex-math notation="LaTeX">^1</tex-math> <inline-graphic xlink:href="alazmi-ieq3-2849728.gif"/> </inline-formula>H nuclei. However, the current availability of high magnetic fields and cryogenically cooled probe heads allow researchers to overcome the low sensitivity of <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq4-2849728.gif"/> </inline-formula>C nuclei. Consequently, <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq5-2849728.gif"/> </inline-formula>C-detected experiments have become a popular technique in different NMR applications especially resonance assignment and structure determination of large proteins. In this paper, we propose the first spin system forming method for <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq6-2849728.gif"/> </inline-formula>C-detected NMR spectra. Our method is able to accurately form spin systems based on as few as two <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq7-2849728.gif"/> </inline-formula>C-detected spectra, CBCACON, and CBCANCO. Our method picks slices from the more trusted spectrum and uses them as feedback to direct the slice picking in the less trusted one. This feedback leads to picking the accurate slices that consequently helps to form better spin systems. We tested our method on a real dataset of 'Ubiquitin' and a benchmark simulated dataset consisting of 12 proteins. We fed our spin systems as inputs to a genetic algorithm to generate the chemical shift assignment, and obtained 92 percent correct chemical shift assignment for Ubiquitin. For the simulated dataset, we obtained an average recall of 86 percent and an average precision of 88 percent. Finally, our chemical shift assignment of Ubiquitin was given as an input to CS-ROSETTA server that generated structures close to the experimentally determined structure.
AbstractList Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently, [Formula Omitted]H-detected experiments are the dominant NMR technique used due to the high sensitivity of [Formula Omitted]H nuclei. However, the current availability of high magnetic fields and cryogenically cooled probe heads allow researchers to overcome the low sensitivity of [Formula Omitted]C nuclei. Consequently, [Formula Omitted]C-detected experiments have become a popular technique in different NMR applications especially resonance assignment and structure determination of large proteins. In this paper, we propose the first spin system forming method for [Formula Omitted]C-detected NMR spectra. Our method is able to accurately form spin systems based on as few as two [Formula Omitted]C-detected spectra, CBCACON, and CBCANCO. Our method picks slices from the more trusted spectrum and uses them as feedback to direct the slice picking in the less trusted one. This feedback leads to picking the accurate slices that consequently helps to form better spin systems. We tested our method on a real dataset of ‘Ubiquitin’ and a benchmark simulated dataset consisting of 12 proteins. We fed our spin systems as inputs to a genetic algorithm to generate the chemical shift assignment, and obtained 92 percent correct chemical shift assignment for Ubiquitin. For the simulated dataset, we obtained an average recall of 86 percent and an average precision of 88 percent. Finally, our chemical shift assignment of Ubiquitin was given as an input to CS-ROSETTA server that generated structures close to the experimentally determined structure.
Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently, <inline-formula><tex-math notation="LaTeX">^1</tex-math> <inline-graphic xlink:href="alazmi-ieq2-2849728.gif"/> </inline-formula>H-detected experiments are the dominant NMR technique used due to the high sensitivity of <inline-formula><tex-math notation="LaTeX">^1</tex-math> <inline-graphic xlink:href="alazmi-ieq3-2849728.gif"/> </inline-formula>H nuclei. However, the current availability of high magnetic fields and cryogenically cooled probe heads allow researchers to overcome the low sensitivity of <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq4-2849728.gif"/> </inline-formula>C nuclei. Consequently, <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq5-2849728.gif"/> </inline-formula>C-detected experiments have become a popular technique in different NMR applications especially resonance assignment and structure determination of large proteins. In this paper, we propose the first spin system forming method for <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq6-2849728.gif"/> </inline-formula>C-detected NMR spectra. Our method is able to accurately form spin systems based on as few as two <inline-formula><tex-math notation="LaTeX">^{13}</tex-math> <inline-graphic xlink:href="alazmi-ieq7-2849728.gif"/> </inline-formula>C-detected spectra, CBCACON, and CBCANCO. Our method picks slices from the more trusted spectrum and uses them as feedback to direct the slice picking in the less trusted one. This feedback leads to picking the accurate slices that consequently helps to form better spin systems. We tested our method on a real dataset of 'Ubiquitin' and a benchmark simulated dataset consisting of 12 proteins. We fed our spin systems as inputs to a genetic algorithm to generate the chemical shift assignment, and obtained 92 percent correct chemical shift assignment for Ubiquitin. For the simulated dataset, we obtained an average recall of 86 percent and an average precision of 88 percent. Finally, our chemical shift assignment of Ubiquitin was given as an input to CS-ROSETTA server that generated structures close to the experimentally determined structure.
Author Gao, Xin
Abbas, Ahmed
Alazmi, Meshari
Guo, Xianrong
Fan, Ming
Li, Lihua
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Snippet Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently,...
Nuclear magnetic resonance (NMR) spectroscopy is attracting more attention in the field of computational structural biology. Till recently, [Formula...
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Chemical equilibrium
chemical shift assignment
Chemicals
Computer applications
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denoising spectra
Feedback
Genetic algorithms
Magnetic fields
NMR
Nuclear magnetic resonance
Nuclei
Organic chemistry
protein structure determination
Proteins
Resonance
Sensitivity
Smoothing methods
Spectroscopy
Spectrum analysis
spin systems
Three-dimensional displays
Ubiquitin
Title A Slice-based ^C-detected NMR Spin System Forming and Resonance Assignment Method
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