Buchner Lena, Güntert Peter
Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute of Advanced Studies, Goethe University Frankfurt am Main, Max-von-Laue-Str. 9, 60438, Frankfurt am Main, Germany.
J Biomol NMR. 2015 May;62(1):81-95. doi: 10.1007/s10858-015-9921-z. Epub 2015 Mar 22.
The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but a systematic evaluation of its performance has not yet been reported. In this paper we systematically analyze the reliability of combined automated NOESY assignment and structure calculation with CYANA under a variety of conditions on the basis of the experimental NMR data sets of ten proteins. To evaluate the robustness of the algorithm, the original high-quality experimental data sets were modified in different ways to simulate the effect of data imperfections, i.e. incomplete or erroneous chemical shift assignments, missing NOESY cross peaks, inaccurate peak positions, inaccurate peak intensities, lower dimensionality NOESY spectra, and higher tolerances for the matching of chemical shifts and peak positions. The results show that the algorithm is remarkably robust with regard to imperfections of the NOESY peak lists and the chemical shift tolerances but susceptible to lacking or erroneous resonance assignments, in particular for nuclei that are involved in many NOESY cross peaks.
NOESY交叉峰的自动归属已成为核磁共振蛋白质结构分析的一项基本技术。用于此目的的一种广泛使用的算法在CYANA程序中得以实现。它已被用于大量溶液中蛋白质的结构测定,但尚未有对其性能的系统评估报告。在本文中,我们基于十种蛋白质的实验核磁共振数据集,在各种条件下系统地分析了使用CYANA进行NOESY自动归属与结构计算相结合的可靠性。为评估该算法的稳健性,对原始高质量实验数据集进行了不同方式的修改,以模拟数据缺陷的影响,即化学位移归属不完整或错误、缺少NOESY交叉峰、峰位置不准确、峰强度不准确、低维NOESY谱以及化学位移和峰位置匹配的更高容差。结果表明,该算法对于NOESY峰列表的缺陷和化学位移容差具有显著的稳健性,但易受共振归属缺失或错误的影响,特别是对于涉及许多NOESY交叉峰的原子核。