Friedrichs M S, Mueller L, Wittekind M
Macromolecular NMR Department, Bristol-Myers Squibb Pharmaceutical Research Institute, Princeton, NJ 08543-4000.
J Biomol NMR. 1994 Sep;4(5):703-26. doi: 10.1007/BF00404279.
A computer algorithm that determines the 1HN, 15N, 13C alpha, 1H alpha, 13C beta and 1H beta chemical-shift assignments of protein residues with minimal human intervention is described. The algorithm is implemented as a suite of macros that run under a modified version of the FELIX 1.0 program (Hare Research, Bothell, WA). The input to the algorithm is obtained from six multidimensional, triple-resonance experiments: 3D HNCACB, 3D CBCA(CO)HN, 4D HNCAHA, 4D HN(CO)CAHA, 3D HBHA(CO)NH and 3D HNHA(Gly). For small proteins, the two 4D spectra can be replaced by either the 3D HN(CA)HA, 3D H(CA)NNH, or the 15N-edited TOCSY-HSQC experiments. The algorithm begins by identifying and collecting the intraresidue and sequential resonances of the backbone and 13C beta atoms into groups. These groups are sequentially linked and then assigned to residues by matching the 13C alpha and 13C beta chemical-shift profiles of the linked groups to that of the protein's primary structure. A major strength of the algorithm is its ability to overcome imperfect data, e.g., missing or overlapping peaks. The viability of the procedure is demonstrated with two test cases. In the first, NMR data from the six experiments listed above were used to reassign the backbone resonances of the 93-residue human hnRNP C RNA-binding domain. In the second, a simulated cross-peak list, generated from the published NMR assignments of calmodulin, was used to test the ability of the algorithm to assign the backbone resonances of proteins containing internally homologous segments. Finally, the automated method was used to assign the backbone resonances of apokedarcidin, a previously unassigned, 114-residue protein.
本文描述了一种计算机算法，该算法能够在最少人工干预的情况下确定蛋白质残基的1HN、15N、13Cα、1Hα、13Cβ和1Hβ化学位移归属。该算法以一套宏程序的形式实现，运行于FELIX 1.0程序（华盛顿州博塞尔市Hare Research公司）的修改版本之下。算法的输入数据来自六个多维三共振实验：3D HNCACB、3D CBCA(CO)HN、4D HNCAHA、4D HN(CO)CAHA、3D HBHA(CO)NH和3D HNHA(Gly)。对于小蛋白质，两个4D谱可以用3D HN(CA)HA、3D H(CA)NNH或15N编辑的TOCSY - HSQC实验替代。算法首先将主链和13Cβ原子的残基内及序列共振识别并收集成组。这些组依次相连，然后通过将相连组的13Cα和13Cβ化学位移谱与蛋白质一级结构的谱进行匹配来归属到残基。该算法的一个主要优势在于其克服不完美数据（如缺失或重叠峰）的能力。通过两个测试案例证明了该程序的可行性。在第一个案例中，使用上述六个实验的NMR数据重新归属93个残基的人hnRNP C RNA结合结构域的主链共振。在第二个案例中，从钙调蛋白已发表的NMR归属生成的模拟交叉峰列表用于测试该算法归属含有内部同源片段的蛋白质主链共振的能力。最后，使用该自动化方法归属了阿波德卡菌素（一种先前未归属的114个残基的蛋白质）的主链共振。
