重新审视:从交叉相关弛豫率确定总体旋转相关时间的代数解决方案

IF 1.3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Scott A. Robson, Çağdaş Dağ, Hongwei Wu, Joshua J. Ziarek
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引用次数: 5

摘要

准确的旋转相关时间(\({\tau }_{\text{c}}\))对于快速时间尺度核磁共振动力学的定量分析至关重要。随着分子质量的增加,使用横向和纵向弛豫速率的经典推导\({\tau }_{c}\)变得越来越不合适,因为远距离偶极子-偶极子相互作用对纵向弛豫的贡献很大。使用交叉相关弛豫实验的推导,如TRACT,克服了这些限制,但在65中计算错误% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S2 ≈ 0.9 to further improve the accuracy of \({\tau }_{\text{c}}\) estimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H–N internuclear distance (\(r\)), difference of the two principal components of the axially-symmetric 15N CSA tensor (\(\Delta {\delta }_{N}\)), and angle of the CSA tensor relative to the N–H bond vector (\(\theta\)). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated relaxation rates

Accurate rotational correlation times (\({\tau }_{\text{c}}\)) are critical for quantitative analysis of fast timescale NMR dynamics. As molecular weights increase, the classic derivation of \({\tau }_{c}\) using transverse and longitudinal relaxation rates becomes increasingly unsuitable due to the non-trivial contribution of remote dipole–dipole interactions to longitudinal relaxation. Derivations using cross-correlated relaxation experiments, such as TRACT, overcome these limitations but are erroneously calculated in 65% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S2 ≈ 0.9 to further improve the accuracy of \({\tau }_{\text{c}}\) estimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H–N internuclear distance (\(r\)), difference of the two principal components of the axially-symmetric 15N CSA tensor (\(\Delta {\delta }_{N}\)), and angle of the CSA tensor relative to the N–H bond vector (\(\theta\)). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment.

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来源期刊
Journal of Biomolecular NMR
Journal of Biomolecular NMR 生物-光谱学
CiteScore
6.00
自引率
3.70%
发文量
19
审稿时长
6-12 weeks
期刊介绍: The Journal of Biomolecular NMR provides a forum for publishing research on technical developments and innovative applications of nuclear magnetic resonance spectroscopy for the study of structure and dynamic properties of biopolymers in solution, liquid crystals, solids and mixed environments, e.g., attached to membranes. This may include: Three-dimensional structure determination of biological macromolecules (polypeptides/proteins, DNA, RNA, oligosaccharides) by NMR. New NMR techniques for studies of biological macromolecules. Novel approaches to computer-aided automated analysis of multidimensional NMR spectra. Computational methods for the structural interpretation of NMR data, including structure refinement. Comparisons of structures determined by NMR with those obtained by other methods, e.g. by diffraction techniques with protein single crystals. New techniques of sample preparation for NMR experiments (biosynthetic and chemical methods for isotope labeling, preparation of nutrients for biosynthetic isotope labeling, etc.). An NMR characterization of the products must be included.
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