Protein solution structure determination using distances from two-dimensional nuclear Overhauser effect experiments: effect of approximations on the accuracy of derived structures.
Protein solution structure determination using distances from two-dimensional nuclear Overhauser effect experiments: effect of approximations on the accuracy of derived structures.
复制标题
使用二维核奥弗豪塞效应实验的距离确定蛋白质溶液结构：近似值对衍生结构准确性的影响。
DOI：
10.1073/pnas.88.4.1237
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发表时间：
1991
影响因子：
11.1
通讯作者：
James,TL
中科院分区：
文献类型：
--
作者：
Thomas,PD;Basus,VJ;James,TL
迄今为止，许多蛋白质的溶液结构已利用从二维核奥弗豪塞效应 (2D NOE) 谱估计的质子间距离约束来确定。尽管通常使用的简单的孤立自旋对近似（ISPA）可能会导致距离的系统误差，但大量的约束使得能够以相当高的分辨率定义蛋白质结构。检查这些系统误差对所得蛋白质结构的影响。迭代弛豫矩阵计算可以解释分子中所有质子之间的偶极相互作用，可以在很少或没有分子结构先验知识的情况下准确确定核间距离。还解决了这种额外复杂性的价值。为了评估这些距离确定方法，针对任意“真实”蛋白质结构计算假设的“实验”数据，包括随机噪声和峰重叠。研究了从 2D NOE 峰值强度获取距离约束的三种方法：一种需要保守使用 ISPA，一种假设 ISPA 相当准确，另一种利用本实验室开发的称为 MARDIGRAS（用于辨别水性结构几何形状的松弛矩阵分析）的迭代松弛矩阵方法。使用距离几何算法为每个距离集生成一系列结构。每个家庭的平均结构质量都很好。使用限制性更强的 ISPA 方法（而不是更保守的 ISPA 方法），平均结构与真实结构的均方根偏差提高了约 2-5%。以保守方式（即初始模型较差）使用 MARDIGRAS 可使均方根偏差改善 8-15%。凭借更好的初始模型，MARDIGRAS 获得了更准确的距离。 MARDIGRAS 还允许在较长的混合时间内分析 2D NOE 数据，从而产生额外的距离。然而，使用更严格的 ISPA 距离确实会导致蛋白质局部区域出现一些系统性不正确的结构特征，产生 2-3 A 的畸变。实验数据和结构计算光谱之间的比较与均方根偏差相关，从而提供了一种结构评估方法。提出了用于评估实验和计算的 2D NOE 强度之间拟合度的 R 因子。
Solution structures for many proteins have been determined to date utilizing interproton distance constraints estimated from two-dimensional nuclear Overhauser effect (2D NOE) spectra. Although the simple isolated spin pair approximation (ISPA) generally used can result in systematic errors in distances, the large number of constraints enables protein structure to be defined with reasonably high resolution. Effects of these systematic errors on the resulting protein structure are examined. Iterative relaxation matrix calculations, which account for dipolar interactions between all protons in a molecule, can accurately determine internuclear distances with little or no a priori knowledge of the molecular structure. The value of this additional complexity is also addressed. To assess these distance determination methods, hypothetical "experimental" data, including random noise and peak overlap, are calculated for an arbitrary "true" protein structure. Three methods of obtaining distance constraints from 2D NOE peak intensities are examined: one entails a conservative use of ISPA, one assumes the ISPA to be fairly accurate, and one utilizes an iterative relaxation matrix method called MARDIGRAS (matrix analysis of relaxation for discerning the geometry of an aqueous structure), developed in this laboratory. A distance geometry algorithm was used to generate a family of structures for each distance set. The quality of the average structure from each family was good. The root-mean-square deviation of that average structure from the true structure was improved about 2-5% using the more restrictive rather than the more conservative ISPA approach. Use of MARDIGRAS in a conservative fashion--i.e., with a poor initial model--resulted in improvement in the root-mean-square deviation by 8-15%. With a better initial model, MARDIGRAS obtained even more accurate distances. MARDIGRAS also permits analysis of 2D NOE data at longer mixing times, yielding additional distances. Use of more restrictive ISPA distances did, however, result in a few systematically incorrect structural features in local regions of the protein, producing distortions of 2-3 A. Comparison between experimental data and spectra calculated for the structures correlates with root-mean-square deviation, offering a method of structure evaluation. An R factor for evaluating fit between experimental and calculated 2D NOE intensities is proposed.