Discovering and Manipulating Macromolecular Conformational Ensembles

项目总结 大分子在构象系综的不同结构状态之间波动。其中一个主要的 配体和突变的影响是改变这些不同状态的相对稳定性。然而，大多数 我们的结构生物学模型围绕着不同和单一结构的范例。我们的主要目标是 是超越生物大分子的静态图像，同时保留询问 由此产生的模型可以改进配基设计和突变工程。我们也有兴趣创造 用实验方法来扰动这些构象的相对种群，使用温度或 化学扰动将它们带入窗口，在那里它们可以被观察和模拟。在之前的两年中 在NIGMS的支持下，我们专注于三项主要技术：1)集合建模，其中 X射线(现在，越来越多地，低温EM)密度图中存在的替代构象明确地 确认并提炼为构象系综或多构象模型；2)多温度 结晶学，在避免辐射损害的同时，X射线数据收集的温度被转移到 改变不同种群的相对平衡；3)模型验证，其中特定点的密度为 量化以支持或证伪建模。我们已经广泛和协作地应用了这些范例， 致力于开放的方法和软件。两个主要关注点是：1)使用组合发现配体 多温结晶学和经验X射线碎片筛选(最显著的是确定新方法 变构抑制磷酸酶PTP1B)；2)蛋白质突变工程(在上下文中最显著的 蛋白质设计和理解构象动力学和催化之间的关系)。使用 Mira的支持下，我们将继续我们的计算开发，以进一步改进对 替代构象，对配体结合对蛋白质构象的影响进行大规模测试 异质性，以改进对不同集合模式类型的验证和比较，并量化密度 可供选择的构象、氢和修饰信号。同时，我们的试验性工作将 关注对抗抗生素耐药性的新配体的结构基础和定义构象 低聚合酶谷氨酰胺合成酶的景观。我们的实验工作提供了一个重要的 为新的计算创新和验证新建模替代方案的重要性的方法进行试验 构象。米拉的支持还将使我们能够以透明和公开的方式进行研究， 进一步致力于早期数据披露(例如，我们网站上的预印本和帖子)和数据重用 (例如，初级衍射和EM数据的沉积)，这已经通过使其他 研究人员。总而言之，我们的研究将创建强大的实验和计算方法来访问 构象集合，并提供了利用构象异质性达到有用目的的途径。

PROJECT SUMMARY Macromolecules fluctuate between different structural states of a conformational ensemble. One of the major effects of ligands and mutations is to change the relative stability of these different states. However, most of our structural biology modeling revolves around a paradigm of distinct and singular structures. Our major goal is to move beyond static images of biological macromolecules, while retaining the ability to interrogate the resulting models to improve ligand design and mutational engineering. We are also interested in creating experimental methods to perturb the relative populations of these conformations, using temperature or chemical perturbation to bring them into the window where they can be observed and modeled. In two previous grants supported by NIGMS, we have focused three primary technologies: 1) ensemble modeling, where alternative conformations present in X-ray (and now, increasingly, cryoEM) density maps are explicitly identified and refined as a conformational ensemble or multiconformer model; 2) multitemperature crystallography, where the temperature of X-ray data collection is shifted, while avoiding radiation damage, to change the relative balance of different populations; 3) model validation, where the density at specific points is quantified to support or falsify modelling. We have applied these paradigms broadly and collaboratively, with a commitment to open methods and software. Two major foci have been: 1) ligand discovery using combinations of multitemperature crystallography and empirical X-ray fragment screening (most notably to identify new ways to allosterically inhibit the phosphatase PTP1B); 2) protein mutational engineering (most notably in the context of protein design and in understanding the relationship between conformation dynamics and catalysis). With MIRA support, we will continue our computational developments to further improve cryoEM modeling of alternative conformations, to perform large scale test of the effects of ligand binding on protein conformational heterogeneity, to improve validation and comparison of distinct ensemble model types, and to quantify density signals for alternative conformations, hydrogens, and modifications. In parallel, our experimental work will focus on the structural basis of new ligands to counter antibiotic resistance and on defining the conformational landscape of the oligomeric enzyme glutamine synthetase. Our experimental work provides an important testbed for new computational innovations and ways to validate the importance of newly modeled alternative conformations. MIRA support will also enable us to conduct our research in a transparent and open manner, dedicating ourselves further into early data disclosure (e.g. preprints and posts on our website) and data reuse (e.g. deposition of primary diffraction and EM data), which are already paying dividends by enabling other researchers. In summary, our research will create robust experimental and computational methods to access conformational ensembles and provide avenues to exploit conformational heterogeneity for useful ends.