We have previously reported on the measurement of exact NOEs (eNOEs), which yield a wealth of additional information in comparison to conventional NOEs. We have used these eNOEs in a variety of applications, including calculating high-resolution structures of proteins and RNA molecules. The collection of eNOEs is challenging, however, due to the need to measure a NOESY buildup series consisting of typically four NOESY spectra with varying mixing times in a single measurement session. While the 2D version can be completed in a few days, a fully sampled 3D-NOESY buildup series can take 10 days or more to acquire. This can be both expensive as well as problematic in the case of samples that are not stable over such a long period of time. One potential method to significantly decrease the required measurement time of eNOEs is to use non-uniform sampling (NUS) to decrease the number of points measured in the indirect dimensions. The effect of NUS on the extremely tight distance restraints extracted from eNOEs may be very pronounced. Therefore, we investigated the fidelity of eNOEs measured from three test cases at decreasing NUS densities: the 18.4 kDa protein human Pin1, the 4.1 kDa WW domain of Pin1 (both in 3D), and a 4.6 kDa 14mer RNA UUCG tetraloop (2D). Our results show that NUS imparted negligible error on the eNOE distances derived from good quality data down to 10% sampling for all three cases, but there is a noticeable decrease in the eNOE yield that is dependent upon the underlying sparsity, and thus complexity, of the sample. For Pin1, this transition occurred at roughly 40% while for the WW domain and the UUCG tetraloop it occurred at lower NUS densities of 20% and 10%, respectively. We rationalized these numbers through reconstruction simulations under various conditions. The extent of this loss depends upon the number of scans taken as well as the number of peaks to be reconstructed. Based on these findings, we have created guidelines for choosing an optimal NUS density depending on the number of peaks needed to be reconstructed in the densest region of a 2D or 3D NOESY spectrum.

我们之前曾报道过精确 NOE (eNOE) 的测量，与传统 NOE 相比，它产生了大量的附加信息。我们已在各种应用中使用这些 eNOE，包括计算蛋白质和 RNA 分子的高分辨率结构。然而，eNOE 的收集具有挑战性，因为需要测量一个 NOESY 累积系列，该系列通常由四个 NOESY 光谱组成，在单个测量会话中具有不同的混合时间。虽然 2D 版本可以在几天内完成，但完整采样的 3D-NOESY 构建系列可能需要 10 天或更长时间才能获得。如果样品在如此长的时间内不稳定，这可能既昂贵又存在问题。显着减少 eNOE 所需测量时间的一种潜在方法是使用非均匀采样 (NUS) 来减少间接维度中测量的点数。NUS 对从 eNOE 中提取的极窄距离约束的影响可能非常明显。因此，我们研究了在 NUS 密度降低的三个测试案例中测量的 eNOE 的保真度：18.4 kDa 蛋白质人 Pin1、Pin1 的 4.1 kDa WW 域（均为 3D）和 4.6 kDa 14mer RNA UUCG 四环 (2D)。我们的结果表明，对于所有三种情况，NUS 对源自高质量数据的 eNOE 距离的误差可忽略不计，低至 10% 的采样率，但 eNOE 产量显着下降，这取决于潜在的稀疏性，因此复杂性样本。对于引脚 1，这种转变发生在大约 40% 处，而对于 WW 结构域和 UUCG 四环，它分别发生在 20% 和 10% 的较低 NUS 密度下。我们通过在各种条件下的重建模拟使这些数字合理化。这种损失的程度取决于所进行的扫描次数以及要重建的峰值的数量。基于这些发现，我们创建了根据需要在 2D 或 3D NOESY 光谱的最密集区域重建的峰数来选择最佳 NUS 密度的指南。这种损失的程度取决于所进行的扫描次数以及要重建的峰值的数量。基于这些发现，我们创建了根据需要在 2D 或 3D NOESY 光谱的最密集区域重建的峰数来选择最佳 NUS 密度的指南。这种损失的程度取决于所进行的扫描次数以及要重建的峰值的数量。基于这些发现，我们创建了根据需要在 2D 或 3D NOESY 光谱的最密集区域重建的峰数来选择最佳 NUS 密度的指南。