A combined transmembrane topology and signal peptide prediction method
A combined transmembrane topology and signal peptide prediction method
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DOI：
10.1016/j.jmb.2004.03.016
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发表时间：
2004-05-14
影响因子：
5.6
通讯作者：
Sonnhammer, ELL
中科院分区：
文献类型：
--
作者：
Käll, L;Krogh, A;Sonnhammer, ELL
跨膜蛋白拓扑结构预测和信号肽预测中一个固有的问题是跨膜螺旋的疏水区域和信号肽的疏水区域高度相似，导致这两种预测之间产生交叉反应。因此，为了进一步改进预测，构建一个旨在区分这两类的预测工具是很重要的。此外，当成功预测出引导跨膜蛋白的信号肽时，可以获得拓扑结构信息，因为这表明成熟蛋白的N端必须位于膜的非细胞质一侧。在此，我们介绍Phobius，一种结合了跨膜蛋白拓扑结构和信号肽预测的工具。该预测工具基于隐马尔可夫模型（HMM），它通过一系列相互连接的状态对信号肽的不同序列区域以及跨膜蛋白的不同区域进行建模。训练是在一个新组装和整理的数据集上进行的。与TMHMM和SignalP相比，Phobius大幅减少了跨膜区段和信号肽之间交叉预测产生的错误。信号肽的错误分类从26.1%降低到3.9%，跨膜螺旋的错误分类从19.0%降低到7.7%。Phobius被应用于智人和大肠杆菌的蛋白质组。在这里我们还注意到与TMHMM/SignalP相比错误分类大幅减少，这表明Phobius非常适合用于信号肽和跨膜区域的全基因组注释。该方法可在http://phobius.cgb.ki.se/以及http://phobius.binf.ku.dk/获取。（C）2004 Elsevier Ltd.保留所有权利。
An inherent problem in transmembrane protein topology prediction and signal peptide prediction is the high similarity between the hydrophobic regions of a transmembrane helix and that of a signal peptide, leading to cross-reaction between the two types of predictions. To improve predictions further, it is therefore important to make a predictor that aims to discriminate between the two classes. In addition, topology information can be gained when successfully predicting a signal Peptide leading a trans' membrane protein since it dictates that the N terminus of the mature protein must be on the non-cytoplasmic side of the membrane. Here, we present Phobius, a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states. Training was done on a newly assembled and curated dataset. Compared to TMHMM and SignalP, errors coming from cross-prediction between transmembrane segments and signal peptides were reduced substantially by Phobius. False classifications of signal peptides were reduced from 26.1% to 3.9% and false classifications of transmembrane helices were reduced from 19.0%, to 7.7%. Phobius was applied to the proteomes of Honzo sapiens and Escherichia coli. Here we also noted a drastic reduction of false classifications compared to TMHMM/SignalP, suggesting that Phobius is well suited for whole-genome annotation of signal peptides and transmembrane regions. The method is available at http://phobius.cgb.ki.se/ as well as at http://phobius.binf.ku.dk/ (C) 2004 Elsevier Ltd. All rights reserved.