Centre of New Technologies, University of Warsaw, Warsaw, Poland.
Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland.
PLoS Comput Biol. 2022 Oct 6;18(10):e1010258. doi: 10.1371/journal.pcbi.1010258. eCollection 2022 Oct.
NMR spectroscopy is key in the study of intrinsically disordered proteins (IDPs). Yet, even the first step in such an analysis-the assignment of observed resonances to particular nuclei-is often problematic due to low peak dispersion in the spectra of IDPs. We show that the assignment process can be aided by finding "hidden" chemical shift patterns specific to the amino acid residue types. We find such patterns in the training data from the Biological Magnetic Resonance Bank using linear discriminant analysis, and then use them to classify spin systems in an α-synuclein sample prepared by us. We describe two situations in which the procedure can greatly facilitate the analysis of NMR spectra. The first involves the mapping of spin systems chains onto the protein sequence, which is part of the assignment procedure-a prerequisite for any NMR-based protein analysis. In the second, the method supports assignment transfer between similar samples. We conducted experiments to demonstrate these cases, and both times the majority of spin systems could be unambiguously assigned to the correct residue types.
NMR 光谱学是研究无规卷曲蛋白质(IDP)的关键。然而,即使在这种分析的第一步——将观察到的共振分配给特定的核——由于 IDP 谱中的峰分散度低,通常也会出现问题。我们表明,通过找到特定于氨基酸残基类型的“隐藏”化学位移模式,可以帮助分配过程。我们使用线性判别分析在生物磁共振库的训练数据中找到这些模式,然后使用它们对我们制备的α-突触核蛋白样本中的自旋系统进行分类。我们描述了两种情况下,该程序可以极大地促进 NMR 光谱分析。第一种情况涉及将自旋系统链映射到蛋白质序列上,这是分配过程的一部分——这是任何基于 NMR 的蛋白质分析的前提。在第二种情况下,该方法支持在类似样本之间进行分配转移。我们进行了实验来证明这些情况,在这两种情况下,大多数自旋系统都可以明确地分配给正确的残基类型。