Computational Structural Biology, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands.
J Biomol NMR. 2013 Sep;57(1):27-35. doi: 10.1007/s10858-013-9762-6. Epub 2013 Aug 3.
We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70 % of the cases. All structures that passed the reliability filter were accurate (<2 Å RMSD from the reference).
我们报告了在仅使用化学位移核磁共振数据计算蛋白质结构方面的进展。我们之前开发的方法 CS-Rosetta 使用化学位移和序列信息从大型蛋白质结构库中挑选短的蛋白质片段库来组装结构。在这里，我们证明了新的和改进的片段选择器与迭代采样算法 RASREC 的结合可以显著提高收敛速度和准确性。此外，我们引入了改进的标准来评估该方法生成的模型的准确性。该方法在 50-100 残基大小范围内的 39 个蛋白质上进行了测试，在 70%的情况下生成可靠的结构。通过可靠性筛选的所有结构都是准确的（与参考值的 RMSD<2 Å）。
