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通过迭代模板优化(ITR)识别相关蛋白质。

Recognition of related proteins by iterative template refinement (ITR).

作者信息

Yi T M, Lander E S

机构信息

Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge 02142.

出版信息

Protein Sci. 1994 Aug;3(8):1315-28. doi: 10.1002/pro.5560030818.

Abstract

Predicting the structural fold of a protein is an important and challenging problem. Available computer programs for determining whether a protein sequence is compatible with a known 3-dimensional structure fall into 2 categories: (1) structure-based methods, in which structural features such as local conformation and solvent accessibility are encoded in a template, and (2) sequence-based methods, in which aligned sequences of a set of related proteins are encoded in a template. In both cases, the programs use a static template based on a predetermined set of proteins. Here, we describe a computer-based method, called iterative template refinement (ITR), that uses templates combining structure-based and sequence-based information and employs an iterative search procedure to detect related proteins and sequentially add them to the templates. Starting from a single protein of known structure, ITR performs sequential cycles of database search to construct an expanding tree of templates with the aim of identifying subtle relationships among proteins. Evaluating the performance of ITR on 6 proteins, we found that the method automatically identified a variety of subtle structural similarities to other proteins. For example, the method identified structural similarity between arabinose-binding protein and phosphofructokinase, a relationship that has not been widely recognized.

摘要

预测蛋白质的结构折叠是一个重要且具有挑战性的问题。现有的用于确定蛋白质序列是否与已知三维结构兼容的计算机程序可分为两类:(1)基于结构的方法,其中诸如局部构象和溶剂可及性等结构特征被编码在一个模板中;(2)基于序列的方法,其中一组相关蛋白质的比对序列被编码在一个模板中。在这两种情况下,程序都使用基于一组预先确定的蛋白质的静态模板。在此,我们描述一种基于计算机的方法,称为迭代模板优化(ITR),它使用结合了基于结构和基于序列信息的模板,并采用迭代搜索程序来检测相关蛋白质并将它们依次添加到模板中。从一个已知结构的单一蛋白质开始,ITR执行数据库搜索的连续循环,以构建一个不断扩展的模板树,目的是识别蛋白质之间的细微关系。通过评估ITR在6种蛋白质上的性能,我们发现该方法自动识别出了与其他蛋白质的各种细微结构相似性。例如,该方法识别出了阿拉伯糖结合蛋白和磷酸果糖激酶之间的结构相似性,这种关系尚未得到广泛认可。

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