Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, Goethe University Frankfurt am Main, 60438 Frankfurt am Main, Germany.
Laboratory of Chemical Physics, NIDDK, National Institutes of Health, Bethesda, MD 20892, USA.
Prog Nucl Magn Reson Spectrosc. 2020 Jun-Aug;118-119:54-73. doi: 10.1016/j.pnmrs.2020.04.001. Epub 2020 Apr 24.
As structural biology trends towards larger and more complex biomolecular targets, a detailed understanding of their interactions and underlying structures and dynamics is required. The development of methyl-TROSY has enabled NMR spectroscopy to provide atomic-resolution insight into the mechanisms of large molecular assemblies in solution. However, the applicability of methyl-TROSY has been hindered by the laborious and time-consuming resonance assignment process, typically performed with domain fragmentation, site-directed mutagenesis, and analysis of NOE data in the context of a crystal structure. In response, several structure-based automatic methyl assignment strategies have been developed over the past decade. Here, we present a comprehensive analysis of all available methods and compare their input data requirements, algorithmic strategies, and reported performance. In general, the methods fall into two categories: those that primarily rely on inter-methyl NOEs, and those that utilize methyl PRE- and PCS-based restraints. We discuss their advantages and limitations, and highlight the potential benefits from standardizing and combining different methods.
随着结构生物学向更大和更复杂的生物分子靶标发展,需要深入了解它们的相互作用以及潜在的结构和动态。甲基-TROSY 的发展使 NMR 光谱学能够提供原子分辨率的见解,了解溶液中大型分子组装的机制。然而,甲基-TROSY 的适用性受到繁琐和耗时的共振分配过程的阻碍,通常通过域碎片化、定点突变和在晶体结构背景下分析 NOE 数据来完成。作为回应,在过去十年中开发了几种基于结构的自动甲基分配策略。在这里,我们全面分析了所有可用的方法,并比较了它们的输入数据要求、算法策略和报告的性能。一般来说,这些方法分为两类:主要依赖于甲基间 NOE 的方法,以及利用基于甲基 PRE 和 PCS 的约束的方法。我们讨论了它们的优缺点,并强调了标准化和组合不同方法的潜在好处。