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Local Protein Threading by Mixed Integer Programming

机译:通过混合整数编程实现局部蛋白质线程化

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摘要

During the last decade, significant progresses have been made in solving the Protein Threading Problem (PTP). However, all previous approaches to PTP only perform global sequence–structure alignment. This obvious limitation is in clear contrast with the ”world of sequences”, where local sequence-sequence alignments are widely used to find functionally important regions in families of proteins. This paper presents a novel approach to PTP which allows to align a part of a protein structure onto a protein sequence in order to detect local similarities. We show experimentally that such local sequence–structure alignments improve the quality of the prediction. Our approach is based on Mixed Integer Programming (MIP) which has been shown to be very successful in this domain. We describe five MIP models for local sequence–structure alignments, compare and analyze their performances by using ILOG CPLEX 10 solver on a benchmark of proteins.
机译:在过去的十年中,在解决蛋白质穿线问题(PTP)方面取得了重大进展。但是,所有以前的PTP方法仅执行全局序列结构比对。这种明显的局限性与“序列世界”形成鲜明对比,在“序列世界”中,局部序列-序列比对被广泛用于发现蛋白质家族中功能上重要的区域。本文提出了一种新的PTP方法,该方法允许将蛋白质结构的一部分与蛋白质序列对齐,以检测局部相似性。我们通过实验证明,这种局部序列-结构比对可以提高预测的质量。我们的方法基于混合整数编程(MIP),已证明在该领域非常成功。我们描述了五个用于局部序列-结构比对的MIP模型,通过在蛋白质基准上使用ILOG CPLEX 10解算器来比较和分析它们的性能。

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