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

项目摘要 X射线晶体学和cryoEM单粒子重建（cryoEM SPR）生成独特详细的 结构信息，用于：（1）在分子水平上理解细胞过程，（2）解释和 验证其他生物化学、生物物理学和细胞生物学方法获得的结果，以及（3）指导药物设计 问题研究所有这些应用都与NIH的使命高度相关。该提案旨在推进数据分析 用于X射线和cryoEM衍射以及cryoEM SPR的方法， 可以用这两种技术从微米和纳米晶体以及从单分子（颗粒）获得 用电子显微镜。 PI旨在通过高度分层的方法将X射线晶体学和cryoEM SPR方法扩展到新的领域 数据挖掘和降维方法的应用。最近的数据丰富性 硬件的变化使人们能够深入探索更复杂的非随机启动算法， 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。 在衍射方法中，人们经常需要将来自多个晶体的数据联合收割机以获得成功的结构 溶液然而，最佳平均值应仅考虑代表相同结构来源的数据。 衍射图案，所以有一个基本的需要，隔离个别样品成不同的群体， 内部同晶。在传统的方法中，复杂的非同构模式导致组合 数据分析的复杂性，存在不完整性和低信噪比， 数据集。PI将开发解决这个长期未解决问题的方法，这些方法具有 也有可能推进对生物学相关结构变异性的分析，这些变异性表现为非生物学相关性。 在实验数据中同构。在cryoEM衍射中，数据分析尚未产生可靠的结构 结果一致，从头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，绝对构型的确定仍然是一个挑战。PI将 开发和实施实验和计算解决方案，以推进系统效应的建模 在电子衍射中遇到的问题，并扩展电子晶体学中的定相方法，以解决 这些突出问题。PI还将致力于开发偏倚幅度和去偏倚的估计值 扩展cryoEM SPR的程序，以便可以可靠地模拟更小的颗粒。最后，PI将 开发依赖于比较基因组学的方法，以便能够建立和验证结构模型， 非常低的分辨率，目前超出了分子解释的范围。所有的研究都将依赖于 PI在选定领域的强大专业知识。

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.