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

项目摘要/摘要 大分子结晶学(MX)是一种成熟和广泛使用的方法，用来获得准确、高质量的 生物分子的3D分辨率模型，但MX数据包含尚未解锁的信息。 单电子变化可以在低至3.5？的分辨率下清楚地看到，如果系统误差 被淘汰了。创建能够解释这些错误的模拟技术将对以下方面产生重大影响 三个方面：1)消除结构变化和辐射损害的其他警告，最终 限制给定样本的可用数据量2)改进多晶体平均和比较 通过捕获和校正非同构，这将打开信噪比任意增益的大门， 3)区分竞争激烈的替代解释，例如结合配体的存在或不存在， 通过使用更逼真的溶剂和蛋白质模型创建模拟。迈向无损坏数据 从同步加速器开始，我们将从实施一种新的数据收集开始，我们称之为“X射线绘画” 它利用现代的快速成帧探测器结合了宽束和微束的最佳特性 技术：低剂量对比度和分离晶体的最佳部分。然后我们将增强零剂量 通过精细划分可用光子来处理丰富的时间信息的外推。 我们将在成功的基础上，将现实空间中的非同构纠正为互易空间，从而实现合并 像XFEL这样的不完整数据仍被纳入参数结构因子框架。这些低维的 框架将允许通过拨入所需参数从3D分子结构的连续体中进行选择 值，并且还将应用于参数是已知量的情况，例如时间分辨的， 在实验中控制的温度序列、湿度或其他反应坐标和变量。我们会 根据收集到的数千个不同构的数据集测试这些框架模型 我们的光束线和最佳实践报告。为了能够对实验数据进行可靠的解释，我们将扩展 这些多构象模型与基于模拟的溶剂模型相结合。我们的工作将创建标准协议 用于比较溶剂密度与替代解释，并定量评估每种解释的可能性 模拟的情况与真实的大分子结晶学数据进行了比较。除了区分 在对实验数据的不同解释之间，改进的溶剂模型将增强 了解大分子如何影响其表面附近的其他分子并与其相互作用。 总体而言，我们预计消除这些关键系统错误的好处将对两者都具有变革性 方法利用互补的结构技术，如低温电子显微镜， SAXS、层析成像和电子衍射，特别是将结构数据与 来源多种多样。

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.