展望II:基因组级应用的蛋白质结构预测程序。

Dongsup Kim, Dong Xu, Jun-tao Guo, Kyle Ellrott, Ying Xu
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引用次数: 103

摘要

开发了一种新的折叠识别方法,并将其添加到通用蛋白质结构预测包PROSPECT (http://compbio.ornl.gov/PROSPECT/)中。新方法(PROSPECT II)有四个主要特点。(1)我们开发了一种利用进化信息来评估包括单态和成对能量在内的穿线势的有效方法。(ii)我们开发了一种两阶段的线程策略:(a)使用不考虑两两能量的动态规划线程;(b)考虑所有能量项的折叠识别,包括从动态规划线程对齐中计算的两两能量。(iii)我们开发了一种用于折叠识别的组合z-score方案,该方案考虑了每个能量项的z-score。(iv)基于z分数,我们开发了一个置信度指数,该指数基于对整个FSSP模板的600个查询蛋白线程组成的大型数据集的统计分析,测量预测的可靠性和可能的结构-功能关系。在多个基准集上的测试表明,进化信息和其他新特性大大提高了PROSPECT II的对准精度。我们还证明了PROSPECT II在所有相似度水平上的折叠识别性能明显优于其他任何可用的方法。在折叠识别的敏感性上的提高,特别是在超家族和折叠水平上,使PROSPECT II成为一个可靠的、完全自动化的蛋白质结构和功能预测程序,用于基因组规模的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PROSPECT II: protein structure prediction program for genome-scale applications.

A new method for fold recognition is developed and added to the general protein structure prediction package PROSPECT (http://compbio.ornl.gov/PROSPECT/). The new method (PROSPECT II) has four key features. (i) We have developed an efficient way to utilize the evolutionary information for evaluating the threading potentials including singleton and pairwise energies. (ii) We have developed a two-stage threading strategy: (a) threading using dynamic programming without considering the pairwise energy and (b) fold recognition considering all the energy terms, including the pairwise energy calculated from the dynamic programming threading alignments. (iii) We have developed a combined z-score scheme for fold recognition, which takes into consideration the z-scores of each energy term. (iv) Based on the z-scores, we have developed a confidence index, which measures the reliability of a prediction and a possible structure-function relationship based on a statistical analysis of a large data set consisting of threadings of 600 query proteins against the entire FSSP templates. Tests on several benchmark sets indicate that the evolutionary information and other new features of PROSPECT II greatly improve the alignment accuracy. We also demonstrate that the performance of PROSPECT II on fold recognition is significantly better than any other method available at all levels of similarity. Improvement in the sensitivity of the fold recognition, especially at the superfamily and fold levels, makes PROSPECT II a reliable and fully automated protein structure and function prediction program for genome-scale applications.

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