A model for statistical significance of local similarities in structure
A model for statistical significance of local similarities in structure
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DOI：
10.1016/s0022-2836(03)00045-7
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发表时间：
2003-03-07
影响因子：
5.6
通讯作者：
Russell, RB
中科院分区：
文献类型：
--
作者：
Stark, A;Sunyaev, S;Russell, RB
结构生物学可以为未知功能的蛋白质提供三维结构。当序列或结构的比较不能提示功能时，可以通过发现功能上重要的局部结构模式来获得见解。现有的检测这种模式的方法缺乏广泛应用所需的严格统计数据。在这里，我们推导出一个公式来计算这种模式中原子之间的均方根偏差的统计意义。当与数据库搜索方法相结合时，我们的统计数据允许从噪声中辨别出不同褶皱中的真实功能或结构模式。该方法是高度互补的折叠比较，为新的结构提供功能线索，是检测任何新模式的复发的关键。(C)2003年由Elsevier Science Ltd.出版
Structural biology can provide three-dimensional structures for proteins of unknown function. When sequence or structure comparisons fail to suggest a function, insights can come from discovery of functionally important local structural patterns. Existing methods to detect such patterns lack rigorous statistics needed for widespread application. Here, we derive a formula to calculate statistical significance of the root-mean-square deviation between atoms in such patterns. When combined with a database search method, our statistics permit true functional or structural patterns in different folds to be discerned from noise. The approach is highly complementary to fold comparison for providing functional clues for, new structures, and is key for the detection of recurrences of any new pattern. (C) 2003 Published by Elsevier Science Ltd.