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一种用于蛋白质的快速随机穿线算法。

A fast, stochastic threading algorithm for proteins.

作者信息

Crawford O H

机构信息

Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6480, USA.

出版信息

Bioinformatics. 1999 Jan;15(1):66-71. doi: 10.1093/bioinformatics/15.1.66.

Abstract

MOTIVATION

Sequences for new proteins are being determined at a rapid rate, as a result of the Human Genome Project, and related genome research. The ability to predict the three-dimensional structure of proteins from sequence alone would be useful in discovering and understanding their function. Threading, or fold recognition, aims to predict the tertiary structure of a protein by aligning its amino acid sequence with a large number of structures, and finding the best fit. This approach depends on obtaining good performance from both the scoring function, which simulates the free energy for given trial alignments, and the threading algorithm, which searches for the lowest-score alignment. It appears that current scoring functions and threading algorithms need improvement.

RESULTS

This paper presents a new threading algorithm. Numerical tests demonstrate that it is more powerful than two popular approximate algorithms, and much faster than exact methods.

摘要

动机

由于人类基因组计划及相关基因组研究,新蛋白质的序列正以很快的速度被确定。仅从序列预测蛋白质的三维结构的能力,对于发现和理解其功能将是有用的。穿线法,即折叠识别,旨在通过将蛋白质的氨基酸序列与大量结构进行比对并找到最佳匹配来预测其三级结构。这种方法依赖于评分函数(它模拟给定试验比对的自由能)和穿线算法(它搜索最低分比对)都能有良好表现。目前的评分函数和穿线算法似乎需要改进。

结果

本文提出了一种新的穿线算法。数值测试表明它比两种流行的近似算法更强大,且比精确方法快得多。

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