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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >PROTEIN THREADING WITH PROFILES AND DISTANCE CONSTRAINTS USING CLIQUE BASED ALGORITHMS
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PROTEIN THREADING WITH PROFILES AND DISTANCE CONSTRAINTS USING CLIQUE BASED ALGORITHMS

机译:使用基于CLI的算法对带有特征和距离的蛋白质进行约束

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摘要

With the advent of experimental technologies like chemical cross-linking, it has become possible to obtain distances between specific residues of a newly sequenced protein. These types of experiments usually are less time consuming than X-ray crystallography or NMR. Consequently, it is highly desired to develop a method that incorporates this distance information to improve the performance of protein threading methods. However, protein threading with profiles in which constraints on distances between residues are given is known to be NP-hard. By using the notion of a maximum edge-weight clique finding algorithm, we introduce a more efficient method called FTHREAD for profile threading with distance constraints that is 18 times faster than its predecessor CLIQUETHREAD. Moreover, we also present a novel practical algorithm NTHREAD for profile threading with Non-strict constraints. The overall performance of FTHREAD on a data set shows that although our algorithm uses a simple threading function, our algorithm performs equally well as some of the existing methods. Particularly, when there are some unsatisfied constraints, NTHREAD (Non-strict constraints threading algorithm) performs better than threading with FTHREAD (Strict constraints threading algorithm). We have also analyzed the effects of using a number of distance constraints. This algorithm helps the enhancement of alignment quality between the query sequence and template structure, once the corresponding template structure is determined for the target sequence.
机译:随着化学交联等实验技术的出现,获得新测序蛋白质特定残基之间的距离成为可能。这些类型的实验通常比X射线晶体学或NMR耗时少。因此,非常需要开发一种结合该距离信息以改善蛋白质穿线方法性能的方法。然而,已知其中对残基之间的距离给出限制的概况的蛋白质穿线是NP-困难的。通过使用最大边缘权重集团查找算法的概念,我们引入了一种更有效的方法FTHREAD来进行具有距离约束的轮廓螺纹加工,该方法比其前身CLIQUETHREAD快18倍。此外,我们还提出了一种新颖的实用算法NTHREAD,用于具有非严格约束的配置文件线程。 FTHREAD在数据集上的总体性能表明,尽管我们的算法使用简单的线程功能,但我们的算法与某些现有方法的性能相同。特别是,当存在一些未满足的约束条件时,NTHREAD(非严格约束条件线程化算法)的性能要优于使用FTHREAD(严格约束条件线程化算法)的线程。我们还分析了使用许多距离约束的影响。一旦为目标序列确定了相应的模板结构,该算法将有助于提高查询序列和模板结构之间的比对质量。

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