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首页> 外文期刊>Nucleic Acids Research >Structural details (kinks and non-α conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors
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Structural details (kinks and non-α conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors

机译:跨膜螺旋的结构细节(纽结和非α构象)是螺旋内确定的,可以通过序列模式描述符进行预测

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摘要

One of the promising methods of protein structure prediction involves the use of amino acid sequencederived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular α-helical character (i.e. π-helices, 3_(10)-helices and kinks). A 'search engine' derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above 'noncanonical' helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from α-helicity are encoded locally in sequence patterns only about 7-9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure-function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html.
机译:蛋白质结构预测的有前途的方法之一涉及使用氨基酸序列衍生的模式。在这里,我们报告了通过对多蛋白跨膜片段的残基训练集进行数据挖掘而得到的非简并基序描述符的创建。这些残基对应于短区域,在短区域中与规则的α螺旋特征(即π螺旋,3_(10)螺旋和扭结)存在偏差。从这些基序描述符衍生的“搜索引擎”正确识别并区分了蛋白质一级结构的SwissProt / TrEMBL数据库中包含的上述“非规范”螺旋基序。我们的结果表明,偏离α-螺旋性的序列模式仅编码约7-9个残基,并且可以直接从氨基酸序列通过计算机方法确定。螺旋形习性的这种变化的描述对于理解多蛋白的复杂结构-功能关系和药物发现至关重要。我们当前方法的成功预示着类似预测工具的发展,该预测工具能够仅从序列中识别其他结构基序。此处描述的方法已经实现,可以在Internet上的http://cbcsrv.watson.ibm.com/Ttkw.html上获得。

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