Bernsel Andreas, Viklund Håkan, Falk Jenny, Lindahl Erik, von Heijne Gunnar, Elofsson Arne
Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden.
Proc Natl Acad Sci U S A. 2008 May 20;105(20):7177-81. doi: 10.1073/pnas.0711151105. Epub 2008 May 13.
The current best membrane-protein topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among protein, lipids and water, it should be possible to predict topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based topology predictors. This result suggests that prediction of membrane-protein topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.
当前最佳的膜蛋白拓扑结构预测方法通常基于序列统计,包含数百个在已知膜蛋白拓扑结构上优化的参数。然而,由于跨膜螺旋插入膜中是蛋白质、脂质和水之间分子相互作用的结果,正如20多年前Kyte和Doolittle所提出的,应该可以通过直接基于物理数据的方法来预测拓扑结构。在此,我们提出了两种简单的拓扑结构预测方法,它们使用最近发表的特定位置氨基酸对膜插入自由能贡献的实验尺度,其性能与当前最佳的基于统计的拓扑结构预测器相当。这一结果表明,鉴于最近对转运体肽识别的理解有所改进,直接从第一原理预测膜蛋白的拓扑结构和结构是一个可以实现的目标。