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用于从核磁共振数据推导蛋白质溶液结构的启发式优化方法第一步的验证。

Validation of the first step of the heuristic refinement method for the derivation of solution structures of proteins from NMR data.

作者信息

Lichtarge O, Cornelius C W, Buchanan B G, Jardetzky O

机构信息

Stanford Magnetic Resonance Laboratory, Stanford University Medical Center, California 94305.

出版信息

Proteins. 1987;2(4):340-58. doi: 10.1002/prot.340020409.

Abstract

A new method for the analysis of NMR data in terms of the solution structure of proteins has been developed. The method consists of two steps: first a systematic search of the conformational space to define the region allowed by the initial set of experimental constraints, and second, the narrowing of this region by the introduction of additional constraints and optional refinement procedures. The search of the conformational space is guided by heuristics to make it computationally feasible. The method is therefore called the heuristic refinement method and is coded in an expert system called PROTEAN. The paper describes the validation of the first step of the method using an artificial NMR data set generated from the known crystal structure of sperm whale carbon monoxymyoglobin. It is shown that the initial search procedure yields a low-resolution structure of the myoglobin molecule, accurately reproducing its main topological features, and that the precision of the structure depends on the quality of the initial data set.

摘要

已开发出一种根据蛋白质溶液结构分析核磁共振(NMR)数据的新方法。该方法包括两个步骤:首先,对构象空间进行系统搜索,以确定初始实验约束集所允许的区域;其次,通过引入额外约束和可选的优化程序来缩小该区域。构象空间的搜索由启发式方法引导,以使其在计算上可行。因此,该方法被称为启发式优化方法,并编码在一个名为PROTEAN的专家系统中。本文描述了使用从抹香鲸一氧化碳肌红蛋白已知晶体结构生成的人工NMR数据集对该方法第一步的验证。结果表明,初始搜索程序产生了肌红蛋白分子的低分辨率结构,准确地再现了其主要拓扑特征,并且结构的精度取决于初始数据集的质量。

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