From complex data to complex structures: new methods for structural biology

项目摘要 X射线结晶学和CryoEM单粒子重建(CryoEM SPR)产生独特的细节 结构信息用于：(1)在分子水平上理解细胞过程；(2)解释和 验证通过其他生化、生物物理和细胞生物学方法获得的结果，并(3)指导药物设计 学习。所有这些应用都与NIH的任务高度相关。该提案旨在推进数据分析 X射线和低温电子衍射和低温电子自旋共振的方法，以使可靠和信息丰富的结构模型 可以用这两种技术从微晶和纳米晶中获得，也可以从单分子(颗粒)中获得 用电子显微镜观察。 PI的目标是通过高度层次化将X射线结晶学和低温电子显微镜SPR方法扩展到新的领域 数据挖掘和降维方法的应用。最近产生的数据丰富性 硬件的变化使我们能够深入探索更精细的非随机启动算法，这些算法具有 比计算方法中经常使用的随机开始方法具有更好的收敛性能。 在衍射法中，人们经常需要组合来自多个晶体的数据以获得成功的结构 解决方案。但是，最优平均应该只考虑表示相同结构源的数据 衍射图，因此基本需要将单个样品分成不同的组，这些组 内部同构的。在传统方法中，复杂的非同构模式导致组合 在存在不完整性和低信噪比的情况下进行数据分析的复杂性 数据集。国际和平研究所将制定解决这一长期悬而未决的问题的方法，方法包括 也有可能推进对生物相关结构变异性的分析，这种结构变异性表现为非 实验数据中的同构关系。在低温电磁衍射中，数据分析还不能产生可靠的结构 结果始终如一地，从头开始的结构解决方案仅限于少数项目，其中直接方法可以 对于小分子来说，确定绝对构型仍然是一个挑战。私人侦探将 开发和实施实验和计算解决方案，以改进系统效应的建模 在电子衍射学中遇到的问题，并扩展电子结晶学中的位相方法来解决 这些突出问题。PI还将致力于开发偏差幅度和去偏差的估计器 扩展低温电子显微镜SPR的程序，以便可以可靠地模拟更小的颗粒。最后，PI将 开发依赖比较基因组学的方法，以便在以下位置构建和验证结构模型 非常低的分辨率，目前还不能进行分子解释。所有研究都将依赖于 国际和平研究所在选定的领域拥有强大的专业知识。

Project abstract X-ray crystallography and cryoEM single particle reconstruction (cryoEM SPR) generate uniquely detailed structural information that is used to: (1) understand cellular processes at the molecular level, (2) explain and validate results obtain by other biochemical, biophysical and cell biology methods, and also (3) guide drug design studies. All these applications are highly relevant to the NIH mission. The proposal aims to advance data analysis methods for X-ray and cryoEM diffraction and cryoEM SPR so that reliable and informative structural models can be obtained from micro- and nanocrystals with both techniques as well as from single molecules (particles) with electron microscopy. The PI aims to expand X-ray crystallography and cryoEM SPR methods to new areas by highly hierarchical application of data mining and dimensionality reduction methods. The data richness generated by recent changes in hardware enables deep exploration of much more elaborate, non-random start algorithms that have better convergence than the random start methods that are frequently used in computational approaches. In diffraction methods, one frequently needs to combine data from multiple crystals for successful structure solution. However, optimal averaging should only consider data that represent the same structural source of diffraction patterns, so there is a fundamental need to segregate individual samples into distinct groups that are internally isomorphous. In traditional approaches, complex non-isomorphism patterns result in combinatorial complexity of data analysis in the presence of incompleteness and low signal-to-noise for individually contributing datasets. The PI will develop methods addressing this long-standing unsolved problem, with the methods having potential to also advance the analysis of biologically relevant structural variability that manifests as non- isomorphism in experimental date. In cryoEM diffraction, data analysis does not yet produce reliable structural results consistently, de novo structure solution is limited to a small number of projects where direct methods can be used, and for small molecules, determination of absolute configuration remains a challenge. The PI will develop and implement experimental and computational solutions to advance modeling of systematic effects encountered in electron diffraction and to expand phasing approaches in electron crystallography to address these outstanding problems. The PI will also work on developing estimators of bias magnitude and debiasing procedures to expand cryoEM SPR so that much smaller particles can be modelled reliably. Finally, the PI will develop approaches relying on comparative genomics so that structural models can be built and validated at very low resolution that are currently outside of the reach for molecular interpretation. All research will rely on the strong expertise of the PI in selected areas.