Computational Systems Biology Lab, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602-4712, USA.
Structure. 2011 Apr 13;19(4):484-95. doi: 10.1016/j.str.2011.02.002.
Nuclear magnetic resonance paramagnetic relaxation enhancement (PRE) measures long-range distances to isotopically labeled residues, providing useful constraints for protein structure prediction. The method usually requires labor-intensive conjugation of nitroxide labels to multiple locations on the protein, one at a time. Here a computational procedure, based on protein sequence and simple secondary structure models, is presented to facilitate optimal placement of a minimum number of labels needed to determine the correct topology of a helical transmembrane protein. Tests on DsbB (four helices) using just one label lead to correct topology predictions in four of five cases, with the predicted structures <6 Å to the native structure. Benchmark results using simulated PRE data show that we can generally predict the correct topology for five and six to seven helices using two and three labels, respectively, with an average success rate of 76% and structures of similar precision. The results show promise in facilitating experimentally constrained structure prediction of membrane proteins.
磁共振顺磁弛豫增强（PRE）测量到同位素标记残基的远程距离，为蛋白质结构预测提供了有用的约束。该方法通常需要将氮氧自由基标签费力地连接到蛋白质的多个位置，一次一个。这里提出了一种基于蛋白质序列和简单二级结构模型的计算程序，以方便确定确定螺旋跨膜蛋白正确拓扑结构所需的最少标签数量的最佳位置。仅使用一个标签对 DsbB（四个螺旋）进行测试，在五种情况下有四种能够正确预测拓扑结构，预测结构与天然结构的距离<6 Å。使用模拟 PRE 数据的基准测试结果表明，我们通常可以使用两个和三个标签分别预测五个和六个到七个螺旋的正确拓扑结构，平均成功率为 76%，结构精度相似。这些结果有望促进膜蛋白的实验约束结构预测。
