SATCHMO:: sequence alignment and tree construction using hidden Markov models
SATCHMO:: sequence alignment and tree construction using hidden Markov models
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DOI：
10.1093/bioinformatics/btg158
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发表时间：
2003-07-22
期刊：
影响因子：
5.8
通讯作者：
Sjölander, K
中科院分区：
文献类型：
--
作者：
Edgar, RC;Sjölander, K
动机：如果序列同一性低或存在显著程度的结构差异，则仅基于序列信息比对多个蛋白质是具有挑战性的。我们提出了一种新的算法（SATCHMO），旨在解决这一挑战。SATCHMO同时构建一个树和一组多序列比对，树的每个内部节点一个。给定节点处的比对包含其子树内的所有序列，并预测那些序列中的哪些位置是可比对的，哪些位置是不可比对的。因此，当序列在结构上发散时，对齐的区域通常在从叶到根的路径上变得更短。目前的方法要么将所有位置视为可重复的（例如ClustalW），要么仅比对那些被认为在所有序列中同源的位置（例如profile HMM方法）;相比之下，SATCHMO对不同亚组中的可重复区域做出不同的预测。SATCHMO生成配置文件隐马尔可夫模型在每个节点，这些是用来确定分支顺序，对齐序列和预测结构可重复regions.Results：在实验上的BAliBASE基准比对数据库，SATCHMO被证明执行重复ClustalW和UCSC SAM HMM软件。使用SATCHMO识别蛋白质结构域的结果在钾通道上得到证实，并对肿瘤坏死因子α影响钾电流的机制产生影响。
Motivation: Aligning multiple proteins based on sequence information alone is challenging if sequence identity is low or there is a significant degree of structural divergence. We present a novel algorithm (SATCHMO) that is designed to address this challenge. SATCHMO simultaneously constructs a tree and a set of multiple sequence alignments, one for each internal node of the tree. The alignment at a given node contains all sequences within its sub-tree, and predicts which positions in those sequences are alignable and which are not. Aligned regions therefore typically get shorter on a path from a leaf to the root as sequences diverge in structure. Current methods either regard all positions as alignable (e.g. ClustalW), or align only those positions believed to be homologous across all sequences (e.g. profile HMM methods); by contrast SATCHMO makes different predictions of alignable regions in different subgroups. SATCHMO generates profile hidden Markov models at each node; these are used to determine branching order, to align sequences and to predict structurally alignable regions.Results: In experiments on the BAliBASE benchmark alignment database, SATCHMO is shown to perform comparably to ClustalW and the UCSC SAM HMM software. Results using SATCHMO to identify protein domains are demonstrated on potassium channels, with implications for the mechanism by which tumor necrosis factor alpha affects potassium current.