MemType-2L: A Web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM
MemType-2L: A Web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM
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DOI：
10.1016/j.bbrc.2007.06.027
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发表时间：
2007-08-24
影响因子：
3.1
通讯作者：
Shen, Hong-Bin
中科院分区：
文献类型：
--
作者：
Chou, Kuo-Chen;Shen, Hong-Bin
给定未表征的蛋白质序列，我们如何确定它是否是膜蛋白？如果是，它属于哪种膜蛋白类型？这些问题很重要，因为它们与查询蛋白的生物学功能及其与生物系统中其他分子的相互作用过程密切相关。尤其是，随着蛋白质序列的雪崩在后基因组时代产生的，以及使用生化实验来确定其功能的相对较慢的进展，非常希望开发一种可用于帮助解决这些问题的自动化方法。在这项研究中，已经开发了一个称为memtype-2l的2层预测指标：I ST层预测引擎是将查询蛋白识别为膜或非膜；如果是膜蛋白，则将使用第二层预测引擎自动继续该过程，以在以下八个类别中进一步识别其类型：（1）类型1，（2）类型11，（3）类型111，（（3） 4）IV型，（5）多通，（6）脂质链锚定，（7）GPI锚定和（8）外围。 MEMTYPE-2L通过将蛋白质样品与PSE-PSSM（PSEUDO位置特定得分矩阵）向量合并，并通过包含蛋白质样品，并包含通过融合许多功能强大的单独的OET-KNN（优化的证据理论，优化k-nearest邻居）分类器。 Memtype-2L在通过Jackknife测试和独立数据集测试的新结构的严格数据集中获得的成功率很高，这表明Memtype-2L可能成为非常有用的高吞吐量工具。作为Web服务器，Memtype-2L可以在http：// chou.med.harvard.edu/bioinf/mentype上自由访问。 （c）2007 Elsevier Inc.保留所有权利。
Given an uncharacterized protein sequence, how can we identify whether it is a membrane protein or not? If it is, which membrane protein type it belongs to? These questions are important because they are closely relevant to the biological function of the query protein and to its interaction process with other molecules in a biological system. Particularly, with the avalanche of protein sequences generated in the Post-Genomic Age and the relatively much slower progress in using biochemical experiments to determine their functions, it is highly desired to develop an automated method that can be used to help address these questions. In this study, a 2-layer predictor, called MemType-2L, has been developed: the I st layer prediction engine is to identify a query protein as membrane or non-membrane; if it is a membrane protein, the process will be automatically continued with the 2nd-layer prediction engine to further identify its type among the following eight categories: (1) type 1, (2) type 11, (3) type 111, (4) type IV, (5) multipass, (6) lipid-chain-anchored, (7) GPI-anchored, and (8) peripheral. MemType-2L is featured by incorporating the evolution information through representing the protein samples with the Pse-PSSM (Pseudo Position-Specific Score Matrix) vectors, and by containing an ensemble classifier formed by fusing many powerful individual OET-KNN (Optimized Evidence-Theoretic K-Nearest Neighbor) classifiers. The success rates obtained by MemType-2L on a new-constructed stringent dataset by both the jackknife test and the independent dataset test are quite high, indicating that MemType-2L may become a very useful high throughput tool. As a Web server, MemType-2L is freely accessible to the public at http:// chou.med.harvard.edu/bioinf/MenType. (C) 2007 Elsevier Inc. All rights reserved.