Nilges M
European Molecular Biology Laboratory, Heidelberg, FRG.
J Mol Biol. 1995 Feb 3;245(5):645-60. doi: 10.1006/jmbi.1994.0053.
The distances derived from nuclear Overhauser effect (NOE) spectra are usually converted into three-dimensional structures by computer algorithms loosely termed distance geometry. To a varying degree, these methods require that the distance data is unambiguously assigned to pairs of atoms. Typically, however, there are many NOE crosspeaks that cannot be assigned without some knowledge of the structure. These crosspeaks have to be assigned in an iterative manner, using preliminary structures calculated from the unambiguous crosspeaks. In this paper, I present an alternative to this iterative approach. The ambiguity of an NOE crosspeak is correctly described in terms of the distances between all pairs of protons that may be involved. A simple restraining term is defined in terms of "ambiguous" distance restraints that can allow all possible assignments. A new minimization procedure based on simulated annealing is described that is capable of using highly ambiguous data for ab initio structure calculations. In particular, it is feasible to specify the restraint list directly in terms of the proton chemical shift assignment and the NOE peak table, without having assigned NOE crosspeaks to proton pairs. While the primary aim of this paper is determining the global fold of proteins from NMR data, similar strategies can be used for other types of ambiguous distance data. The application to one example, disulphide bridges with unknown connectivity, is described. Model NOE data were generated from the X-ray crystal structure of a small protein with known chemical shift assignments. Varying degrees of ambiguity in the data were assumed. The method obtained the correct polypeptide fold even when all distance restraints were ambiguous. Thus, the new approach may facilitate structure calculations with data derived from very overlapped spectra. It is also a step towards automating the calculation of structures from NMR data. This could prove especially valuable for data derived from three- and four-dimensional experiments. The approach may also prove useful for model building studies and tertiary structure prediction.
源自核Overhauser效应（NOE）光谱的距离通常通过被宽泛地称为距离几何算法的计算机算法转换为三维结构。在不同程度上，这些方法要求距离数据能明确地分配给原子对。然而，通常存在许多NOE交叉峰，如果没有一些结构方面的知识就无法进行分配。这些交叉峰必须以迭代的方式进行分配，使用从明确的交叉峰计算得到的初步结构。在本文中，我提出了一种替代这种迭代方法的方案。NOE交叉峰的模糊性可以通过所有可能涉及的质子对之间的距离来正确描述。根据“模糊”距离约束定义了一个简单的约束项，它可以允许所有可能的分配。描述了一种基于模拟退火的新的最小化程序，该程序能够使用高度模糊的数据进行从头算结构计算。特别地，直接根据质子化学位移分配和NOE峰表来指定约束列表是可行的，而无需将NOE交叉峰分配给质子对。虽然本文的主要目的是从NMR数据确定蛋白质的整体折叠，但类似的策略可用于其他类型的模糊距离数据。描述了该方法在一个例子中的应用，即连接性未知的二硫键。模拟的NOE数据是从具有已知化学位移分配的小蛋白质的X射线晶体结构生成的。假设数据中存在不同程度的模糊性。即使所有距离约束都是模糊的，该方法也能获得正确的多肽折叠。因此，新方法可能有助于利用来自非常重叠光谱的数据进行结构计算。这也是朝着从NMR数据自动计算结构迈出的一步。这对于从三维和四维实验获得的数据可能特别有价值。该方法对于模型构建研究和三级结构预测也可能有用。
