Barclay Alexander M, Milchberg Moses H, Warmuth Owen A, Tuttle Marcus D, Dennis Christopher J, Schwieters Charles D, Rienstra Chad M
Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Structure. 2025 Feb 6;33(2):381-388.e2. doi: 10.1016/j.str.2024.11.011. Epub 2024 Dec 10.
Amyloid fibrils are protein assemblies that are pathologically linked to neurodegenerative diseases. Fibril structures can aid development of highly specific ligands for diagnostic imaging and therapeutics. Solid-state NMR (SSNMR) is a viable approach to solving fibril structures; however, most SSNMR protocols require manual analysis of extensive spectral data, presenting a major bottleneck to determining structures. Standard automation; routines fall short for symmetric multimeric assemblies like amyloids due to high cross peak degeneracy and the need to account for multiple protein subunits. Here, we employ the probabilistic assignment for structure determination protocol in conjunction with strict; symmetry in Xplor-NIH structure determination software, demonstrating the methodology using data from a previous structure of an α-synuclein (Asyn) fibril implicated in Parkinson disease. The automated protocol generated a structure of comparable, if not superior, quality in a few days of computational time, reducing the manual effort required; to solve amyloid structures by SSNMR.
淀粉样纤维是与神经退行性疾病病理相关的蛋白质聚集体。纤维结构有助于开发用于诊断成像和治疗的高特异性配体。固态核磁共振(SSNMR)是解决纤维结构的一种可行方法;然而,大多数SSNMR方案需要对大量光谱数据进行人工分析,这成为确定结构的一个主要瓶颈。标准的自动化程序对于像淀粉样蛋白这样的对称多聚体组装体来说并不适用,因为交叉峰简并度高且需要考虑多个蛋白质亚基。在这里,我们将用于结构确定的概率分配协议与Xplor-NIH结构确定软件中的严格对称性相结合,使用先前与帕金森病相关的α-突触核蛋白(Asyn)纤维结构的数据来演示该方法。自动协议在几天的计算时间内生成了质量相当(如果不是更优)的结构,减少了通过SSNMR解决淀粉样蛋白结构所需的人工工作量。