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A Monte Carlo/simulated annealing algorithm for sequential resonance assignment in solid state NMR of uniformly labeled proteins with magic-angle spinning

机译:蒙特卡罗/模拟退火算法,用于魔术角旋转均匀标记蛋白质的固态NMR中的顺序共振分配

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摘要

We describe a computational approach to sequential resonance assignment in solid state NMR studies of uniformly ~(15)N,~(13)C-labeled proteins with magic-angle spinning. As input, the algorithm uses only the protein sequence and lists of ~(15)N/~(13)C_α crosspeaks from 2D NCACX and NCOCX spectra that include possible residue-type assignments of each crosspeak. Assignment of crosspeaks to specific residues is carried out by a Monte Carlo/simulated annealing algorithm, implemented in the program MC-ASSIGN1. The algorithm tolerates substantial ambiguity in residue-type assignments and coexistence of visible and invisible segments in the protein sequence. We use MC-ASSIGN1 and our own 2D spectra to replicate and extend the sequential assignments for uniformly-labeled HET-s(218-289) fibrils previously determined manually by Siemer et al. (J. Biomol. NMR, 34 (2006) 75-87) from a more extensive set of 2D and 3D spectra. Accurate assignments by MC-ASSIGN1 do not require data that are of exceptionally high quality. Use of MC-ASSIGN1 (and its extensions to other types of 2D and 3D data) is likely to alleviate many of the difficulties and uncertainties associated with manual resonance assignments in solid state NMR studies of uniformly labeled proteins, where spectral resolution and signal-to-noise are often sub-optimal.
机译:我们描述了一种固态核磁共振研究中均匀〜(15)N,〜(13)C标记的蛋白质的魔角旋转固态共振研究中的顺序共振分配的一种计算方法。作为输入,该算法仅使用蛋白质序列和2D NCACX和NCOCX光谱的〜(15)N /〜(13)C_α交叉峰列表,其中包括每个交叉峰的可能残基类型分配。通过在程序MC-ASSIGN1中实现的蒙特卡罗/模拟退火算法,将交叉峰分配给特定残基。该算法在残基类型分配中以及在蛋白质序列中可见和不可见片段的共存方面具有明显的歧义。我们使用MC-ASSIGN1和我们自己的2D光谱来复制和扩展先前由Siemer等人手动确定的均匀标记的HET-s(218-289)原纤维的顺序分配。 (J.Biomol.NMR,34(2006)75-87)来自更广泛的2D和3D光谱集。 MC-ASSIGN1进行的准确分配不需要非常高质量的数据。 MC-ASSIGN1的使用(及其对其他类型的2D和3D数据的扩展)可能会减轻与均匀标记蛋白质的固态NMR研究中手动共振分配相关的许多困难和不确定性,其中光谱分辨率和信号-噪声通常不是最佳的。

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