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一个根据熵标准从蛋白质中提取的最小受挫α螺旋片段的数据库。

A data base of minimally frustrated alpha helical segments extracted from proteins according to an entropy criterion.

作者信息

Casadio R, Compiani M, Fariselli P, Martelli P L

机构信息

CIRB, Biocomputing Unit, University of Bologna, Italy.

出版信息

Proc Int Conf Intell Syst Mol Biol. 1999:68-76.

Abstract

A data base of minimally frustrated alpha helical segments is defined by filtering a set comprising 822 non redundant proteins, which contain 4783 alpha helical structures. The data base definition is performed using a neural network-based alpha helix predictor, whose outputs are rated according to an entropy criterion. A comparison with the presently available experimental results indicates that a subset of the data base contains the initiation sites of protein folding experimentally detected and also protein fragments which fold into stable isolated alpha helices. This suggests the usage of the data base (and/or of the predictor) to highlight patterns which govern the stability of alpha helices in proteins and the helical behavior of isolated protein fragments.

摘要

通过筛选包含822个非冗余蛋白质(其中含有4783个α螺旋结构)的集合来定义一个最小受挫α螺旋片段的数据库。使用基于神经网络的α螺旋预测器进行数据库定义,其输出根据熵标准进行评级。与目前可用的实验结果进行比较表明,该数据库的一个子集包含实验检测到的蛋白质折叠起始位点以及折叠成稳定孤立α螺旋的蛋白质片段。这表明可以使用该数据库(和/或预测器)来突出控制蛋白质中α螺旋稳定性和孤立蛋白质片段螺旋行为的模式。

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