Department of Applied Mathematics, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.
Center for Advanced Mathematics for Energy Research Applications, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.
Proc Natl Acad Sci U S A. 2017 Jul 11;114(28):7222-7227. doi: 10.1073/pnas.1708217114. Epub 2017 Jun 26.
Free-electron lasers now have the ability to collect X-ray diffraction patterns from individual molecules; however, each sample is delivered at unknown orientation and may be in one of several conformational states, each with a different molecular structure. Hit rates are often low, typically around 0.1%, limiting the number of useful images that can be collected. Determining accurate structural information requires classifying and orienting each image, accurately assembling them into a 3D diffraction intensity function, and determining missing phase information. Additionally, single particles typically scatter very few photons, leading to high image noise levels. We develop a multitiered iterative phasing algorithm to reconstruct structural information from single-particle diffraction data by simultaneously determining the states, orientations, intensities, phases, and underlying structure in a single iterative procedure. We leverage real-space constraints on the structure to help guide optimization and reconstruct underlying structure from very few images with excellent global convergence properties. We show that this approach can determine structural resolution beyond what is suggested by standard Shannon sampling arguments for ideal images and is also robust to noise.
自由电子激光现在能够从单个分子中收集 X 射线衍射图谱；然而，每个样本都是以未知的方向提供的，并且可能处于几种构象状态之一，每种状态都具有不同的分子结构。命中率通常很低，通常约为 0.1%，限制了可以收集的有用图像数量。确定准确的结构信息需要对每个图像进行分类和定向，准确地将它们组装成一个 3D 衍射强度函数，并确定缺失的相位信息。此外，单个粒子通常散射很少的光子，导致图像噪声水平很高。我们开发了一种多层次迭代相衬算法，通过在单个迭代过程中同时确定状态、取向、强度、相位和基础结构，从单粒子衍射数据中重建结构信息。我们利用结构的实空间约束来帮助指导优化，并从很少的图像中重建基础结构，具有极好的全局收敛特性。我们表明，这种方法可以确定超出理想图像标准香农采样论点所建议的结构分辨率，并且对噪声也具有鲁棒性。
