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Homolog detection using global sequence properties suggests an alternate view of structural encoding in protein sequences

机译:使用全局序列特性的同源检测可提供蛋白质序列中结构编码的另一种观点

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摘要

We show that a Fourier-based sequence distance function is able to identify structural homologs of target sequences with high accuracy. It is shown that Fourier distances correlate very strongly with independently determined structural distances between molecules, a property of the method that is not attainable using conventional representations. It is further shown that the ability of the Fourier approach to identify protein folds is statistically far in excess of random expectation. It is then shown that, in actual searches for structural homologs of selected target sequences, the Fourier approach gives excellent results. On the basis of these results, we suggest that the global information detected by the Fourier representation is an essential feature of structure encoding in protein sequences and a key to structural homology detection.
机译:我们表明基于傅立叶的序列距离函数能够以高精度识别目标序列的结构同源物。结果表明,傅立叶距离与分子之间独立确定的结构距离密切相关,这是使用常规表示方法无法获得的方法特性。进一步表明,傅立叶方法鉴定蛋白质折叠的能力在统计学上远远超出了随机预期。然后表明,在实际搜索所选靶序列的结构同源物中,傅里叶方法给出了极好的结果。基于这些结果,我们建议通过傅立叶表示法检测到的全局信息是蛋白质序列中结构编码的基本特征,也是结构同源性检测的关键。

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