Multidimensional solid-state NMR spectra of oriented membrane proteins can be used to infer the backbone torsion angles and hence the overall protein fold by measuring dipolar couplings and chemical shift anisotropies, which depend on the orientation of each peptide plane with respect to the external magnetic field. However, multiple peptide plane orientations can be consistent with a given set of angular restraints. This ambiguity is further exacerbated by experimental uncertainty in obtaining and interpreting such restraints. The previously developed algorithms for structure calculations using angular restraints typically involve a sequential walkthrough along the backbone to find the torsion angles between the consecutive peptide plane orientations that are consistent with the experimental data. This method is sensitive to experimental uncertainty in interpreting the peak positions of as low as ± 10 Hz, often yielding high structural RMSDs for the calculated structures. Here we present a significantly improved version of the algorithm which includes the fitting of several peptide planes at once in order to prevent propagation of error along the backbone. In addition, a protocol has been devised for filtering the structural solutions using Rosetta scoring functions in order to find the structures that both fit the spectrum and satisfy bioinformatics restraints. The robustness of the new algorithm has been tested using synthetic angular restraints generated from the known structures for two proteins: a soluble protein 2gb1 (56 residues), chosen for its diverse secondary structure elements, i.e. an alpha-helix and two beta-sheets, and a membrane protein 4a2n, from which the first two transmembrane helices (having a total of 64 residues) have been used. Extensive simulations have been performed by varying the number of fitted planes, experimental error, and the number of NMR dimensions. It has been found that simultaneously fitting two peptide planes always shifted the distribution of the calculated structures toward lower structural RMSD values as compared to fitting a single torsion-angle pair. For each protein, irrespective of the simulation parameters, Rosetta was able to distinguish the most plausible structures, often having structural RMSDs lower than 2 Å with respect to the original structure. This study establishes a framework for de-novo protein structure prediction using a combination of solid-state NMR angular restraints and bioinformatics.

中文翻译：

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使用 Rosetta 验证从 NMR 角度限制计算的蛋白质骨架结构。

定向膜蛋白的多维固态 NMR 光谱可用于通过测量偶极耦合和化学位移各向异性来推断骨架扭转角，从而推断整体蛋白质折叠，这取决于每个肽平面相对于外部磁场的方向. 然而，多个肽平面方向可以与一组给定的角度约束一致。在获得和解释这种限制时的实验不确定性进一步加剧了这种模糊性。先前开发的使用角度约束的结构计算算法通常涉及沿主干的顺序遍历，以找到与实验数据一致的连续肽平面方向之间的扭转角。这种方法在解释低至 ± 10 Hz 的峰值位置时对实验不确定性很敏感，通常会为计算的结构产生高结构 RMSD。在这里，我们提出了一个显着改进的算法版本，其中包括一次拟合多个肽平面，以防止错误沿着主干传播。此外，还设计了一种协议，用于使用 Rosetta 评分函数过滤结构解决方案，以便找到既适合光谱又满足生物信息学限制的结构。新算法的稳健性已经使用从两种蛋白质的已知结构生成的合成角度约束进行了测试：一种可溶性蛋白质 2gb1（56 个残基），因其不同的二级结构元素而被选择，即一个 α-螺旋和两个 β-折叠，和膜蛋白 4a2n，其中前两个跨膜螺旋（总共有 64 个残基）已被使用。通过改变拟合平面的数量、实验误差和 NMR 维度的数量，已经进行了广泛的模拟。已经发现，与拟合单个扭转角对相比，同时拟合两个肽平面总是使计算结构的分布向更低的结构 RMSD 值移动。对于每种蛋白质，无论模拟参数如何，Rosetta 都能够区分最合理的结构，相对于原始结构，其结构 RMSD 通常低于 2 Å。本研究结合使用固态核磁共振角度约束和生物信息学，建立了从头蛋白质结构预测的框架。从中使用了前两个跨膜螺旋（总共有 64 个残基）。通过改变拟合平面的数量、实验误差和 NMR 维度的数量，已经进行了广泛的模拟。已经发现，与拟合单个扭转角对相比，同时拟合两个肽平面总是使计算结构的分布向更低的结构 RMSD 值移动。对于每种蛋白质，无论模拟参数如何，Rosetta 都能够区分最合理的结构，相对于原始结构，其结构 RMSD 通常低于 2 Å。本研究结合使用固态核磁共振角度约束和生物信息学，建立了从头蛋白质结构预测的框架。从中使用了前两个跨膜螺旋（总共有 64 个残基）。通过改变拟合平面的数量、实验误差和 NMR 维度的数量，已经进行了广泛的模拟。已经发现，与拟合单个扭转角对相比，同时拟合两个肽平面总是使计算结构的分布向更低的结构 RMSD 值移动。对于每种蛋白质，无论模拟参数如何，Rosetta 都能够区分最合理的结构，相对于原始结构，其结构 RMSD 通常低于 2 Å。本研究结合使用固态核磁共振角度约束和生物信息学，建立了从头蛋白质结构预测的框架。