CEA, CNRS, and UJF-Grenoble 1, Protein Dynamics and Flexibility, Institut de Biologie Structurale Jean-Pierre Ebel, 41 Rue Jules Horowitz, Grenoble 38027, France.
J Am Chem Soc. 2012 Sep 12;134(36):15138-48. doi: 10.1021/ja306905s. Epub 2012 Aug 28.
Intrinsically disordered regions are predicted to exist in a significant fraction of proteins encoded in eukaryotic genomes. The high levels of conformational plasticity of this class of proteins endows them with unique capacities to act in functional modes not achievable by folded proteins, but also places their molecular characterization beyond the reach of classical structural biology. New techniques are therefore required to understand the relationship between primary sequence and biological function in this class of proteins. Although dependences of some NMR parameters such as chemical shifts (CSs) or residual dipolar couplings (RDCs) on structural propensity are known, so that sampling regimes are often inferred from experimental observation, there is currently no framework that allows for a statistical mapping of the available Ramachandran space of each amino acid in terms of conformational propensity. In this study we develop such an approach, combining highly efficient conformational sampling with ensemble selection to map the backbone conformational sampling of IDPs on a residue specific level. By systematically analyzing the ability of NMR data to map the conformational landscape of disordered proteins, we identify combinations of RDCs and CSs that can be used to raise conformational degeneracies inherent to different data types, and apply these approaches to characterize the conformational behavior of two intrinsically disordered proteins, the K18 domain from Tau protein and N(TAIL) from measles virus nucleoprotein. In both cases, we identify the enhanced populations of turn and helical regions in key regions of the proteins, as well as contiguous strands that show clear and enhanced polyproline II sampling.
无规则区域被预测存在于真核生物基因组编码的蛋白质的很大一部分中。这类蛋白质具有高度的构象可塑性，使它们具有独特的能力，以实现折叠蛋白质无法实现的功能模式，但也使它们的分子特征超出了经典结构生物学的范围。因此，需要新的技术来理解这一类蛋白质中一级序列和生物功能之间的关系。尽管一些 NMR 参数（如化学位移 (CSs) 或残差偶极耦合 (RDCs)）与结构倾向性之间存在依赖性，因此采样范围通常可以从实验观察中推断出来，但目前还没有框架可以根据构象倾向性对每个氨基酸的可用 Ramachandran 空间进行统计映射。在这项研究中，我们开发了这样一种方法，将高效的构象采样与集合选择相结合，以在残基特异性水平上对 IDPs 的骨架构象采样进行映射。通过系统地分析 NMR 数据在映射无序蛋白质构象景观方面的能力，我们确定了可以用于提高不同数据类型固有的构象简并性的 RDCs 和 CSs 的组合，并将这些方法应用于表征两种无序蛋白质的构象行为，即 Tau 蛋白的 K18 结构域和麻疹病毒核蛋白的 N(TAIL)。在这两种情况下，我们都确定了蛋白质关键区域中转角和螺旋区域的增强种群，以及显示出明显和增强的多脯氨酸 II 采样的连续链。
