Elucidating Angular Protein Motion using Kinetic Ensemble Refinement

项目摘要/摘要 推进对关键蛋白质功能(如酶)背后的原子水平机制的理解 催化和变构调节，重要的是首先阐明蛋白质在 解决方案。为了实现这一长期目标，我们将使用最近开发的动态合奏 一种改变核磁共振数据计算建模方式的方法 来解决蛋白质结构和测量蛋白质运动。核磁共振是最强大的技术之一 阐明蛋白质的结构和动力学。它使他们能够在溶液中进行研究(与x射线不同 结晶学)，并且可以捕捉在室温下发生的关键结构重排(不同于 低温电子显微镜)。然而，尽管有这些优势，但实际应用相对较少。 对解决蛋白质结构的方法背后的一个基本方面的改进，即 原子核Overhauser效应(NOE)实验中原子间距离的计算。这些方法有 在很大程度上仍然是定性的，导致大多数核磁共振结构的原子位置存在很大的不确定性。 此外，磁场几乎完全忽略了角运动和动力学如何影响NOE，导致 原子看起来彼此之间的距离比实际距离远得多。要克服这些重大问题 不足之处，我们将实施和测试新的基于动态集成的精化算法 比以前的方法更准确，更逼真，这两种方法都考虑了角度 运动和动力学。消除很大一部分系统性和随机性的结构性误差 从量化不佳的核磁共振谱中，我们还将整合Fit核磁共振峰值量化所取得的进展 我们实验室最近开发的软件。这些方法将被用来创造更好的实验核磁共振 结构，更详尽的侧链动力学模型，并确定解决方案和 以前所未有的细节呈现出晶态。这项工作将使我们能够更准确地确定 表现出显著波动的蛋白质部分的结构动力学，包括蛋白质活性位点， 调节区域和隐藏的结合位点。这样的知识将促进我们对 蛋白质生物物理学，促进新疗法的合理设计。

PROJECT SUMMARY/ABSTRACT To advance the understanding of atomic-level mechanisms behind critical protein functions like enzyme catalysis and allosteric regulation, it is important to first elucidate a true representation of the protein in solution. In an effort to achieve this long term goal, we will use the recently developed Kinetic Ensemble approach to transform the way in which nuclear magnetic resonance (NMR) data is computationally modeled to solve protein structures and measure protein motions. NMR is one of the most powerful techniques for elucidating the structure and dynamics of proteins. It enables their study in solution (unlike x-ray crystallography) and can capture critical structural rearrangements as they happen at room temperature (unlike cryo-electron microscopy). However, despite these advantages, there have been relatively few practical improvements to one of the foundational aspects behind the way protein structures are solved, namely the calculation of interatomic distances from nuclear Overhauser effect (NOE) experiments. Such methods have remained largely qualitative, resulting in large uncertainties in the atomic positions for most NMR structures. Also, the field has almost completely ignored how angular motion and kinetics affect the NOE, resulting in atoms appearing much further away from one another than they actually are. To overcome these significant deficiencies, we will implement and test new Kinetic Ensemble-based refinement algorithms that are considerably more accurate and physically realistic than previous approaches, accounting for both angular motion and kinetics. To eliminate a significant fraction of the systematic and random structural errors resulting from poorly quantified NMR spectra, we will also integrate advances made by the FitNMR peak quantification software recently developed by our lab. These methods will be used to create better experimental NMR structures, more exhaustive models of side chain dynamics, and determine differences between solution and crystal states with unprecedented detail. This work will allow much more accurate determination of the structural dynamics in parts of the protein exhibiting significant fluctuations, including protein active sites, regulatory regions, and hidden binding sites. Such knowledge will advance our fundamental understanding of protein biophysics and facilitate rational design of new therapeutics.