Institute for Molecular Biology and Biophysics, ETH Zürich, 8093, Zürich, Switzerland.
J Biomol NMR. 2012 Feb;52(2):179-90. doi: 10.1007/s10858-011-9600-7. Epub 2012 Jan 18.
Chemical shifts reflect the structural environment of a certain nucleus and can be used to extract structural and dynamic information. Proper calibration is indispensable to extract such information from chemical shifts. Whereas a variety of procedures exist to verify the chemical shift calibration for proteins, no such procedure is available for RNAs to date. We present here a procedure to analyze and correct the calibration of (13)C NMR data of RNAs. Our procedure uses five (13)C chemical shifts as a reference, each of them found in a narrow shift range in most datasets deposited in the Biological Magnetic Resonance Bank. In 49 datasets we could evaluate the (13)C calibration and detect errors or inconsistencies in RNA (13)C chemical shifts based on these chemical shift reference values. More than half of the datasets (27 out of those 49) were found to be improperly referenced or contained inconsistencies. This large inconsistency rate possibly explains that no clear structure-(13)C chemical shift relationship has emerged for RNA so far. We were able to recalibrate or correct 17 datasets resulting in 39 usable (13)C datasets. 6 new datasets from our lab were used to verify our method increasing the database to 45 usable datasets. We can now search for structure-chemical shift relationships with this improved list of (13)C chemical shift data. This is demonstrated by a clear relationship between ribose (13)C shifts and the sugar pucker, which can be used to predict a C2'- or C3'-endo conformation of the ribose with high accuracy. The improved quality of the chemical shift data allows statistical analysis with the potential to facilitate assignment procedures, and the extraction of restraints for structure calculations of RNA.
化学位移反映了特定核的结构环境，可以用于提取结构和动态信息。为了从化学位移中提取这些信息，正确的校准是必不可少的。虽然有多种程序可用于验证蛋白质的化学位移校准，但迄今为止，还没有适用于 RNA 的程序。我们在这里介绍一种分析和纠正 RNA 的 (13)C NMR 数据校准的程序。我们的程序使用五个 (13)C 化学位移作为参考，每个化学位移都在大多数保存在生物磁共振银行中的数据集的狭窄位移范围内找到。在 49 个数据集，我们可以评估 (13)C 校准，并根据这些化学位移参考值检测 RNA (13)C 化学位移中的错误或不一致。超过一半的数据集（49 个中的 27 个）被发现参考不当或包含不一致性。这种高不一致率可能解释了为什么迄今为止，RNA 没有出现明确的结构-(13)C 化学位移关系。我们能够重新校准或纠正 17 个数据集，从而得到 39 个可用的 (13)C 数据集。我们实验室的 6 个新数据集被用于验证我们的方法，将数据库增加到 45 个可用数据集。现在，我们可以使用这个改进后的 (13)C 化学位移数据集来搜索结构-化学位移关系。这通过核糖 (13)C 位移与糖构象之间的清晰关系得到证明，这可以用于高精度地预测核糖的 C2'-或 C3'-内消旋构象。化学位移数据的质量提高允许进行统计分析，并有潜力促进 RNA 结构计算的分配程序和约束提取。
