首页> 外文期刊>Journal of Biomolecular NMR >Linear analysis of carbon-13 chemical shift differences and its application to the detection and correction of errors in referencing and spin system identifications
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Linear analysis of carbon-13 chemical shift differences and its application to the detection and correction of errors in referencing and spin system identifications

机译:碳13化学位移差异的线性分析及其在参考和自旋系统识别中的错误检测和纠正中的应用

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Statistical analysis reveals that the set of differences between the secondary shifts of the alpha- and beta-carbons for residues i of a protein (Delta delta(13)C(i)(alpha) - Delta delta(13)C(i)(beta)) provides the means to detect and correct referencing errors for H-1 and C-13 nuclei within a given dataset. In a correctly referenced protein dataset, linear regression plots of Delta delta(13)C(i)(alpha); Delta delta(13)C(i)(beta), or Delta delta(1)H(i)(alpha) vs. (Delta delta(13)C(i)(alpha) - Delta delta(13)C(i)(beta)) pass through the origin from two directions, the helix-to-coil and strand-to-coil directions. Thus, linear analysis of chemical shifts (LACS) can be used to detect referencing errors and to recalibrate the H-1 and C-13 chemical shift scales if needed. The analysis requires only that the signals be identified with distinct residue types (intra-residue spin systems). LACS allows errors in calibration to be detected and corrected in advance of sequence-specific assignments and secondary structure determinations. Signals that do not fit the linear model (outliers) deserve scrutiny since they could represent errors in identifying signals with a particular residue, or interesting features such as a cis-peptide bond. LACS provides the basis for the automated detection of such features and for testing reassignment hypotheses. Early detection and correction of errors in referencing and spin system identifications can improve the speed and accuracy of chemical shift assignments and secondary structure determinations. We have used LACS to create a database of offset-corrected chemical shifts corresponding to nearly 1800 BMRB entries: similar to 300 with and similar to 1500 without corresponding three-dimensional (3D) structures. This database can serve as a resource for future analysis of the effects of amino acid sequence and protein secondary and tertiary structure on NMR chemical shifts.
机译:统计分析表明,蛋白质残基i(δδ(13)C(i)(α)-δδ(13)C(i)( beta))提供了一种方法,可以检测和纠正给定数据集中H-1和C-13核的参考误差。在正确引用的蛋白质数据集中,Delta delta(13)C(i)α的线性回归图; Delta Delta(13)C(i)β或Delta Delta(1)H(i)α与(Delta Delta(13)C(i)α-Delta Delta(13)C(i )(β)从两个方向穿过原点,即螺旋至线圈方向和钢绞线至线圈方向。因此,化学位移的线性分析(LACS)可用于检测参考误差,并在需要时重新校准H-1和C-13化学位移标度。分析仅要求以不同的残基类型(残基内旋转系统)识别信号。 LACS允许在特定于序列的分配和二级结构确定之前检测并纠正校准错误。不适合线性模型(异常值)的信号值得仔细检查,因为它们可能代表识别带有特定残基或有趣特征(例如顺式肽键)的信号时出现错误。 LACS为自动检测此类功能和测试重新分配假设提供了基础。尽早发现并纠正参考和旋转系统识别中的错误可以提高化学位移分配和二级结构确定的速度和准确性。我们已经使用LACS创建了一个偏移校正的化学位移数据库,该数据库对应于将近1800个BMRB条目:与300相似,在没有对应的三维(3D)结构的情况下与1500相似。该数据库可以用作将来分析氨基酸序列和蛋白质二级和三级结构对NMR化学位移的影响的资源。

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