Eliminating Critical Systematic Errors In Structural Biology With Next-Generation Simulation

项目总结/摘要 大分子晶体学（MX）是一种已建立并广泛使用的方法，用于获得准确、高纯度的晶体。 高分辨率的生物分子3D模型，但MX数据包含尚未解锁的信息。 如果系统误差可以忽略，单电子变化可以在低至3.5 μ m的分辨率下清晰可见。 淘汰创建能够解释这些错误的仿真技术将对 三个方面：1）消除结构变化和其他辐射损害的警告， 2）改进多晶体平均和比较 通过捕获和校正非同构，这将打开通向信噪比中任意增益的大门， 3)区分激烈争论的替代解释，如结合配体的存在或不存在， 通过用更真实的溶剂和蛋白质模型来创建模拟。迈向无损坏数据 从同步加速器开始，我们将实施一种新的数据收集，我们称之为“用X射线绘画” 利用现代快速分幅探测器，将宽波束和微波束的最佳特性联合收割机结合起来 技术：低剂量对比度和晶体最佳部分的隔离。然后我们将加强零剂量 外推以处理通过精细划分可用光子而可用的丰富的时间信息。 我们将建立在我们的成功纠正非同构在真实的空间到互惠空间，使合并 不完整的数据，如XFEL仍然到参数结构因子框架。这些低维的 框架将允许通过拨入所需参数从连续的3D分子结构中进行选择 值，并且还将应用于参数是已知量的情况，例如时间分辨的， 温度系列、湿度或实验中控制的其他反应坐标和变量。我们将 测试这些框架模型对数以千计的非同构数据集已收集在 我们的光束线和最佳实践报告。为了使实验数据的强大解释，我们将扩展 这些多构象模型与基于模拟的溶剂模型。我们的工作将建立标准协议 用于将溶剂密度与其他解释进行比较，并定量评估每种解释的可能性 将模拟的情况与真实的大分子晶体学数据进行比较。除了区分 在对实验数据的不同解释之间，改进溶剂模型将提高 了解大分子如何影响和相互作用与其他分子在其表面附近。 总的来说，我们希望消除这些关键的系统性错误的好处对双方都是变革性的。 方法开发和功能研究，使用互补的结构技术，如CryoEM， SAXS、层析成像和电子衍射，特别是将来自以下的结构数据联合收割机 多个来源。

PROJECT SUMMARY/ABSTRACT Macromolecular Crystallography (MX) is an established and widely used method for obtaining accurate, high- resolution 3D models of biological molecules, yet MX data contain information that has yet to be unlocked. Single-electron changes can be clearly visible at resolutions as low as 3.5 Å if systematic errors can be eliminated. Creating simulation technologies that can account for these errors will have significant impact on three fronts: 1) eliminating the structural changes and other caveats of radiation damage, which ultimately limits the amount of data available from a given sample 2) improving multi-crystal averaging and comparison by capturing and correcting non-isomorphism, which will open the gateway to arbitrary gains in signal-to-noise, 3) discriminating hotly contested alternative interpretations such as the presence or absence of a bound ligand, by creating simulations with more realistic solvent and protein models. To move towards damage-free data from a synchrotron, we will start by implementing a new kind of data collection we call “painting with X-rays” that leverages modern fast-framing detectors to combine the best features of broad-beam and micro-beam technologies: low dose contrast and isolation of the best parts of the crystal. We will then enhance zero-dose extrapolation to handle the rich temporal information made available by finely dividing up the available photons. We will build on our success correcting non-isomorphism in real space into reciprocal space, enabling merging of incomplete data such as XFEL stills into parametric structure factor frameworks. These low-dimensional frameworks will allow selection from a continuum of 3D molecular structures by dialing in desired parameter values, and will also be applied to cases where the parameters are known quantities, such as time-resolved, temperature series, humidity, or other reaction coordinates and variables controlled in an experiment. We will test these framework models against the thousands of non-isomorphous data sets that have been collected at our beamline and report on best practice. To enable robust interpretation of experimental data, we will extend these multi-conformer models with simulation-based solvent models. Our work will create standard protocols for comparing solvent density to alternative interpretations and to quantitatively assess how likely each simulated situation is compared to the real macromolecular crystallography data. In addition to distinguishing between different interpretations of the experimental data, improving solvent models will enhance understanding of how macromolecules influence and interact with other molecules near their surface. Collectively, we expect the benefits of eliminating these critical systematic errors to be transformative to both methods development and functional studies using complimentary structural techniques, such as CryoEM, SAXS, tomography and electron diffraction, especially hybrid methods that combine structural data from multiple sources.