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从核磁共振(NMR)或X射线衍射数据推导空间蛋白质结构。

On deriving spatial protein structure from NMR or X-ray diffraction data.

作者信息

van Gunsteren W F, Gros P, Torda A E, Berendsen H J, van Schaik R C

机构信息

Department of Physical Chemistry, Swiss Federal Institute of Technology Zürich, Switzerland.

出版信息

Ciba Found Symp. 1991;161:150-9; discussion 159-66.

PMID:1814692
Abstract

During the last decade it has become possible to derive the spatial structure of small proteins in solution using multidimensional NMR spectroscopy measurements and interpreting the data in terms of a chemical atomic model. The NMR experiments generate a set of interproton distance constraints, which is subsequently used to generate spatial structures that satisfy the experimental data. Correspondingly, crystallographic least-squares and molecular dynamics refinement is routinely applied to obtain a protein structure that is compatible with the observed structure factor amplitudes. The quality of the structure obtained will depend on the number and quality of the experimental data and on the searching power of the refinement method and protocol. The potential energy annealing conformational search (PEACS) algorithm is shown to be an improvement over standard molecular dynamics search methods. The use of time-dependent distance or structure factor restraints in molecular dynamics refinement yields a much better representation of experimental information than the fixed, static restraints which have generally been used until now. Conventional structure refinement methods lead to a too static and rigid picture of a protein in solution or in the crystalline state.

摘要

在过去十年中,利用多维核磁共振光谱测量并根据化学原子模型解释数据,已能够推导溶液中小蛋白质的空间结构。核磁共振实验生成了一组质子间距离约束条件,随后用于生成满足实验数据的空间结构。相应地,晶体学最小二乘法和分子动力学精修法被常规应用于获得与观测到的结构因子振幅相匹配的蛋白质结构。所获得结构的质量将取决于实验数据的数量和质量,以及精修方法和方案的搜索能力。结果表明,势能退火构象搜索(PEACS)算法比标准分子动力学搜索方法有所改进。在分子动力学精修中使用随时间变化的距离或结构因子约束,比迄今普遍使用的固定静态约束能更好地体现实验信息。传统的结构精修方法导致对处于溶液或晶体状态的蛋白质呈现出过于静态和僵化的描述。

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