Yu J Q, Blumenthal D S, Borer P N
Department of Chemistry, Syracuse University, New York 13244-4100, USA.
J Chem Inf Comput Sci. 1995 Sep-Oct;35(5):803-5. doi: 10.1021/ci00027a002.
An analysis of errors has been done with the Monte Carlo method for natural abundance 13C-NMR relaxation studies of a DNA duplex. Repeated measurements of the longitudinal relaxation time, T1, and the heteronuclear NOE were made at 90.6 MHz on the duplexed DNA pentanucleotide, [d(TCGCG)]2. The deviations averaged over all carbons were 13% for T1 and 9% for NOE. These relative deviations were applied to generate 100 values of T1 and NOE with normal distributions about the measured mean values for each carbon. A new version of MOLDYN, called McMOLDYN, has been written, which was used to generate 100 values of T1 and NOE with normal distributions corresponding to the measured errors; the same error distributions were also applied to measurements at 125.8 MHz. The order parameter, S2, and the effective internal correlation time, tau e, in the Model-Free Approach have been optimized from the distributions simulated by McMOLDYN. McMOLDYN also permits the automated entry of multiple sets of initial guesses for the output parameters S2, tau e, and tau m. In addition, McMOLDYN adds cross-relaxation terms from chemical shift anisotropy, increasingly important as spectrometer magnetic fields get higher. Between the two parameters optimized, S2 has the smallest relative error, estimated at 15% on average, which means that S2 is a well-defined parameter. However, tau e is very poorly defined with the average relative error estimated 85%; it is typically found in the range of 30-300 ps.
已使用蒙特卡罗方法对DNA双链体的天然丰度13C-NMR弛豫研究进行了误差分析。在90.6 MHz下对双链DNA五核苷酸[d(TCGCG)]2进行了纵向弛豫时间T1和异核NOE的重复测量。所有碳的平均偏差T1为13%，NOE为9%。这些相对偏差用于生成100个T1和NOE值，其围绕每个碳的测量平均值呈正态分布的值。编写了一个名为McMOLDYN的MOLDYN新版本，用于生成100个T1和NOE值，其正态分布对应于测量误差；相同的误差分布也应用于125.8 MHz的测量。在无模型方法中的序参数S2和有效内部相关时间tau e已根据McMOLDYN模拟的分布进行了优化。McMOLDYN还允许自动输入输出参数S2、tau e和tau m的多组初始猜测值。此外，McMOLDYN添加了来自化学位移各向异性的交叉弛豫项，随着光谱仪磁场升高，其重要性日益增加。在优化的两个参数之间，S2的相对误差最小，平均估计为15%，这意味着S2是一个定义明确的参数。然而，tau e的定义非常差，平均相对误差估计为85%；它通常在30 - 300 ps范围内。
