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用于识别包含DNA结合螺旋-转角-螺旋基序的蛋白质结构的统计模型。

Statistical models for discerning protein structures containing the DNA-binding helix-turn-helix motif.

作者信息

McLaughlin William A, Berman Helen M

机构信息

Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway 08854-8087, USA.

出版信息

J Mol Biol. 2003 Jun 27;330(1):43-55. doi: 10.1016/s0022-2836(03)00532-1.

DOI:10.1016/s0022-2836(03)00532-1
PMID:12818201
Abstract

A method for discerning protein structures containing the DNA-binding helix-turn-helix (HTH) motif has been developed. The method uses statistical models based on geometrical measurements of the motif. With a decision tree model, key structural features required for DNA binding were identified. These include a high average solvent-accessibility of residues within the recognition helix and a conserved hydrophobic interaction between the recognition helix and the second alpha helix preceding it. The Protein Data Bank was searched using a more accurate model of the motif created using the Adaboost algorithm to identify structures that have a high probability of containing the motif, including those that had not been reported previously.

摘要

一种用于识别包含DNA结合螺旋-转角-螺旋(HTH)基序的蛋白质结构的方法已被开发出来。该方法使用基于该基序几何测量的统计模型。通过决策树模型,确定了DNA结合所需的关键结构特征。这些特征包括识别螺旋内残基的高平均溶剂可及性,以及识别螺旋与其前面的第二个α螺旋之间保守的疏水相互作用。使用通过Adaboost算法创建的更精确的基序模型在蛋白质数据库中进行搜索,以识别极有可能包含该基序的结构,包括那些以前未被报道过的结构。

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