Improving the accuracy of transmembrane protein topology prediction using evolutionary information
Improving the accuracy of transmembrane protein topology prediction using evolutionary information
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DOI：
10.1093/bioinformatics/btl677
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发表时间：
2007-03-01
期刊：
影响因子：
5.8
通讯作者：
Jones, David T.
中科院分区：
文献类型：
--
作者：
Jones, David T.
动机：许多重要的生物学过程如细胞信号传导、膜不透性分子的转运、细胞间通讯、细胞识别和细胞粘附都是由膜蛋白介导的。不幸的是，由于这些蛋白质不溶于水，很难通过实验确定它们的结构。因此，预测这些蛋白质结构的改进方法在生物学研究中至关重要。为了提高跨膜拓扑结构预测，我们评估综合使用的信号肽预测和进化信息在一个单一的algorithm.Results：一个新的方法（MEMSAT 3）预测跨膜蛋白质的拓扑结构从序列配置文件的描述和基准充分交叉验证的标准数据集上的184个跨膜蛋白。该方法被发现预测正确的拓扑结构和跨膜段的位置为80%的测试集。相比之下，其他流行方法在同一基准上的准确率为62-72%。通过使用第二个神经网络专门区分跨膜蛋白和球状蛋白，在检测跨膜蛋白时也可以实现非常低的总体假阳性率（0.5%）。http://bioinf.cs.ucl.ac.uk/memsat www.psipred.net服务器和源代码文件对非商业用户免费。基准和培训数据也可从http://bioinf.cs.ucl.ac.uk/memsat.Contact：dtj@cs.ucl.ac.uk获得。
Motivation: Many important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion are mediated by membrane proteins. Unfortunately, as these proteins are not water soluble, it is extremely hard to experimentally determine their structure. Therefore, improved methods for predicting the structure of these proteins are vital in biological research. In order to improve transmembrane topology prediction, we evaluate the combined use of both integrated signal peptide prediction and evolutionary information in a single algorithm.Results: A new method (MEMSAT3) for predicting transmembrane protein topology from sequence profiles is described and benchmarked with full cross-validation on a standard data set of 184 transmembrane proteins. The method is found to predict both the correct topology and the locations of transmembrane segments for 80% of the test set. This compares with accuracies of 62-72% for other popular methods on the same benchmark. By using a second neural network specifically to discriminate transmembrane from globular proteins, a very low overall false positive rate (0.5%) can also be achieved in detecting transmembrane proteins.Availability: An implementation of the described method is available both as a web server (http://www.psipred.net) and as downloadable source code from http://bioinf.cs.ucl.ac.uk/memsat. Both the server and source code files are free to non-commercial users. Benchmark and training data are also available from http://bioinf.cs.ucl.ac.uk/memsat.Contact: dtj@cs.ucl.ac.uk.