Gregory D M, Benzinger T L, Burkoth T S, Miller-Auer H, Lynn D G, Meredith S C, Botto R E
Chemistry Division, Argonne National Laboratory, IL 60439, USA.
Solid State Nucl Magn Reson. 1998 Dec;13(3):149-66. doi: 10.1016/s0926-2040(98)00086-1.
We demonstrate a new method for investigating the structure of self-associating biopolymers using dipolar recoupling NMR techniques. This approach was applied to the study of fibrillar beta-amyloid (Abeta) peptides (the primary component of the plaques of Alzheimer's disease) containing only a single isotopic spin label (13C), by employing the DRAWS (dipolar recoupling with a windowless sequence) technique to measure 13C-13C distances. The 'single-label' approach simplified analysis of DRAWS data, since only interstrand contacts are present, without the possibility of any intrastrand contacts. As previously reported [T.L.S. Benzinger, D.M. Gregory, T.S. Burkoth, H. Miller-Auer, D.G. Lynn, R.E. Botto, S.C. Meredith, Proc. Natl. Acad. Sci. 95 (1998) 13407.], contacts of approximately 5 A were observed at all residues studied, consistent with an extended parallel beta-sheet structure with each amino acid in exact register. Here, we propose that our strategy is completely generalizable, and provides a new approach for characterizing any iterative, self-associating biopolymer. Towards the end of generalizing and refining our approach, in this paper we evaluate several issues raised by our previous analyses. First, we consider the effects of double-quantum (DQ) transverse relaxation processes. Next, we discuss the effects of various multiple-spin geometries on modeling of DRAWS data. Several practical issues are also discussed: these include (1) the use of DQ filtering experiments, either to corroborate DRAWS data, or as a rapid screening assessment of the proper placement of isotopic spin labels; and (2) the comparison of solid samples prepared by either lyophilization or freezing. Finally, data obtained from the use of single labels is compared with that obtained in doubly 13C-labeled model compounds of known crystal structure. It is shown that such data are obtainable in far more complex peptide molecules. These data,taken together, refine the DRAWS method, and demonstrate its precision and utility in obtaining high resolution structural data in complex biomolecular aggregates such as Abeta.
我们展示了一种使用偶极重耦核磁共振技术研究自缔合生物聚合物结构的新方法。该方法应用于仅含有单个同位素自旋标记（¹³C）的纤维状β-淀粉样蛋白（Aβ）肽（阿尔茨海默病斑块的主要成分）的研究，通过采用DRAWS（无窗口序列偶极重耦）技术来测量¹³C-¹³C距离。“单标记”方法简化了DRAWS数据的分析，因为只存在链间接触，不存在任何链内接触的可能性。如先前报道[T.L.S. 本辛格、D.M. 格雷戈里、T.S. 布尔科斯、H. 米勒 - 奥尔、D.G. 林恩、R.E. 博托、S.C. 梅雷迪思，《美国国家科学院院刊》95 (1998) 13407]，在所有研究的残基处都观察到约5埃的接触，这与具有精确对齐的每个氨基酸的延伸平行β-折叠结构一致。在此，我们提出我们的策略完全可推广，并为表征任何迭代的、自缔合生物聚合物提供了一种新方法。在推广和完善我们的方法的过程中，在本文中我们评估了先前分析中提出的几个问题。首先，我们考虑双量子（DQ）横向弛豫过程的影响。接下来，我们讨论各种多自旋几何结构对DRAWS数据建模的影响。还讨论了几个实际问题：这些问题包括（1）使用DQ滤波实验，要么用于证实DRAWS数据，要么作为对同位素自旋标记正确位置的快速筛选评估；以及（2）比较通过冻干或冷冻制备的固体样品。最后，将使用单标记获得的数据与在已知晶体结构的双¹³C标记模型化合物中获得的数据进行比较。结果表明，这样的数据在更为复杂的肽分子中也可获得。这些数据综合起来，完善了DRAWS方法，并证明了其在获得诸如Aβ等复杂生物分子聚集体的高分辨率结构数据方面的精度和实用性。
