Forrest Lucy R, Tang Christopher L, Honig Barry
Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York 10032, USA.
Biophys J. 2006 Jul 15;91(2):508-17. doi: 10.1529/biophysj.106.082313. Epub 2006 Apr 28.
In this study, we investigate the extent to which techniques for homology modeling that were developed for water-soluble proteins are appropriate for membrane proteins as well. To this end we present an assessment of current strategies for homology modeling of membrane proteins and introduce a benchmark data set of homologous membrane protein structures, called HOMEP. First, we use HOMEP to reveal the relationship between sequence identity and structural similarity in membrane proteins. This analysis indicates that homology modeling is at least as applicable to membrane proteins as it is to water-soluble proteins and that acceptable models (with C alpha-RMSD values to the native of 2 A or less in the transmembrane regions) may be obtained for template sequence identities of 30% or higher if an accurate alignment of the sequences is used. Second, we show that secondary-structure prediction algorithms that were developed for water-soluble proteins perform approximately as well for membrane proteins. Third, we provide a comparison of a set of commonly used sequence alignment algorithms as applied to membrane proteins. We find that high-accuracy alignments of membrane protein sequences can be obtained using state-of-the-art profile-to-profile methods that were developed for water-soluble proteins. Improvements are observed when weights derived from the secondary structure of the query and the template are used in the scoring of the alignment, a result which relies on the accuracy of the secondary-structure prediction of the query sequence. The most accurate alignments were obtained using template profiles constructed with the aid of structural alignments. In contrast, a simple sequence-to-sequence alignment algorithm, using a membrane protein-specific substitution matrix, shows no improvement in alignment accuracy. We suggest that profile-to-profile alignment methods should be adopted to maximize the accuracy of homology models of membrane proteins.
在本研究中,我们调查了为水溶性蛋白质开发的同源建模技术对膜蛋白的适用程度。为此,我们对当前膜蛋白同源建模策略进行了评估,并引入了一个名为HOMEP的同源膜蛋白结构基准数据集。首先,我们使用HOMEP揭示膜蛋白中序列同一性与结构相似性之间的关系。该分析表明,同源建模对膜蛋白的适用性至少与对水溶性蛋白的适用性相同,并且如果使用序列的精确比对,对于模板序列同一性为30%或更高的情况,可以获得可接受的模型(跨膜区域中Cα-RMSD值与天然结构相差2 Å或更小)。其次,我们表明为水溶性蛋白质开发的二级结构预测算法对膜蛋白的表现也大致相同。第三,我们比较了一组应用于膜蛋白的常用序列比对算法。我们发现,使用为水溶性蛋白质开发的最先进的profile-to-profile方法可以获得膜蛋白序列的高精度比对。当在比对评分中使用从查询序列和模板的二级结构导出的权重时,比对精度有所提高,这一结果依赖于查询序列二级结构预测的准确性。使用借助结构比对构建的模板profile可获得最准确的比对。相比之下,使用膜蛋白特异性替换矩阵的简单序列到序列比对算法在比对精度上没有提高。我们建议应采用profile-to-profile比对方法,以最大限度地提高膜蛋白同源模型的准确性。