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首页> 外文期刊>Journal of Molecular Biology >PROTEIN FOLD RECOGNITION BY MAPPING PREDICTED SECONDARY STRUCTURES
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PROTEIN FOLD RECOGNITION BY MAPPING PREDICTED SECONDARY STRUCTURES

机译：通过映射预期的二级结构进行蛋白质折叠识别

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摘要

A strategy is presented for protein fold recognition from secondary structure assignments (alpha-helix and beta-strand). The method can detect similarities between protein folds in the absence of sequence similarity. Secondary structure mapping first identifies all possible matches (maps) between a query string of secondary structures and the secondary structures of protein domains of known three-dimensional structure. The maps are then passed through a series of structural filters to remove those that do not obey simple rules of protein structure. The surviving maps are ranked by scores from the alignment of predicted and experimental accessibilities. Searches made with secondary structure assignments for a test set of 11 fold-families put the correct sequence-dissimilar fold in the first rank 8/11 times. With cross-validated predictions of secondary structure this drops to 4/11 which compares favourably with the widely used THREADER program (1/11). The structural class is correctly predicted 10/11 times by the method in contrast to 5/11 for THREADER. The new technique obtains comparable accuracy in the alignment of amino acid residues and secondary structure elements. Searches are also performed with published secondary structure predictions for the von-Willebrand factor type A domain, the proteasome 20 S alpha subunit and the phosphotyrosine interaction domain. These searches demonstrate how the method can find the correct fold for a protein from a carefully constructed secondary structure prediction, multiple sequence alignment and distance restraints. Scans with experimentally determined secondary structures and accessibility, recognise the correct fold with high alignment accuracy (86% on secondary structures). This suggests that the accuracy of mapping will improve alongside any improvements in the prediction of secondary structure or accessibility. Application to NMR structure determination is also discussed. (C) 1996 Academic Press Limited [References: 63]
机译：提出了一种从二级结构分配（α-螺旋和β-链）识别蛋白质折叠的策略。该方法可以在不存在序列相似性的情况下检测蛋白质折叠之间的相似性。二级结构映射首先识别二级结构的查询字符串与已知三维结构的蛋白质域的二级结构之间的所有可能匹配（图）。然后将这些图通过一系列结构过滤器，以除去那些不遵循简单蛋白质结构规则的过滤器。幸存的地图根据预测的和实验的可及性的比对按分数排序。使用二级结构分配对11个折叠家族的测试集进行搜索，将正确的序列不同折叠置于第一位8/11倍。通过对二级结构的交叉验证预测，该值下降到4/11，与广泛使用的THREADER程序（1/11）相比，它是有利的。与THREADER的5/11相反，通过该方法可以正确预测结构类10/11次。新技术在氨基酸残基和二级结构元件的比对中获得相当的准确性。还使用已发布的二级结构预测对von-Willebrand因子A型结构域，蛋白酶体20 Sα亚基和磷酸酪氨酸相互作用结构域进行搜索。这些搜索证明了该方法如何从精心构建的二级结构预测，多重序列比对和距离限制中找到蛋白质的正确折叠。使用实验确定的二级结构和可访问性进行扫描，以较高的对齐精度（二级结构上为86％）识别正确的折叠。这表明，映射的准确性将随着二级结构或可访问性预测的提高而提高。还讨论了在NMR结构测定中的应用。 （C）1996 Academic Press Limited [参考号：63]

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