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FCANAL:Structure based protein function prediction method.Application to enzymes and binding proteins

机译:FCANAL:基于结构的蛋白质功能预测方法,在酶和结合蛋白中的应用

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摘要

Structural genomics projects are beginning to produce protein structures with unknown functions,thereby creating a need for high-throughput methods to predict functions.Although sequence-based function prediction methods have been used extensively,structure-based prediction is believed to provide higher specificity and sensitivity because functions are closely related to the three-dimensional structures of functional sites,which are more strongly conserved during evolution than sequence.We have developed FCANAL,a method to predict functions using a score matrix obtained from the distances between C~(alpha) atoms and frequencies of appearance [1],The previous report used key residues predicted from sequence comparisons (motifs).In this report,we have expanded the method to include enzymes and binding proteins with key residues predicted on the basis of three-dimensional structures.Using FCANAL,we constructed score matrices for 31 enzymes.When we applied them to all of the structure entries deposited in the Protein Data Bank,FCANAL could detect functional sites with high accuracy.This suggests that FCANAL will help identify the functions of newly determined structures and pinpoint their functionally important regions.
机译:结构基因组学项目开始产生功能未知的蛋白质结构,因此需要高通量方法来预测功能。尽管基于序列的功能预测方法已被广泛使用,但基于结构的预测被认为具有更高的特异性和敏感性。由于功能与功能位的三维结构密切相关,因此在进化过程中比顺序更保守。我们开发了FCANAL,一种使用从C〜α原子之间的距离获得的得分矩阵来预测功能的方法出现的频率和出现的频率[1],以前的报告使用了通过序列比较预测的关键残基(基序)。在本报告中,我们扩展了方法,将具有关键残基的酶和结合蛋白包括在三维结构的基础上。使用FCANAL,我们为31种酶构建了得分矩阵。将它们应用于所有结构实体时蛋白质数据库中的FCANAL可以准确检测功能位点。这表明FCANAL将有助于识别新确定的结构的功能并查明它们的功能重要区域。

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