通过间接形状匹配梯度流从单粒子冷冻电镜数据中恢复蛋白质构象
Recovering protein conformations from single-particle cryo-EM data via indirect shape matching gradient flows
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中文总结 AI 辅助
本研究提出一种基于李群梯度流的间接形状匹配框架，可直接从单粒子冷冻电镜投影重建蛋白质主链，在合成数据上成功恢复单/多链蛋白质并捕捉构象转变。
中文摘要 AI 辅助
单粒子冷冻电子显微镜将大分子成像为其静电势的大量噪声断层投影。我们直接从这些投影重建蛋白质主链，以原子点云形式，无需先重建三维静电势图。我们将此问题表述为间接形状匹配问题：主链的点云模板发生变形，直至其模拟投影与数据匹配，而结构仅通过成像算子被观测。变形通过李群上的梯度流计算，我们在一般几何场景中推导该框架后，将其适配至单粒子冷冻电子显微镜。在合成数据上，我们恢复了单链及多链蛋白质，并捕捉到构象转变。
英文摘要
Single-particle cryo-electron microscopy images a macromolecule as many noisy tomographic projections of its electrostatic potential. We reconstruct the protein backbone directly from such projections, as an atomic point cloud, without the intermediate step of reconstructing the 3D electrostatic potential map. We formulate this as an indirect shape matching problem: a point-cloud template of the backbone is deformed until its simulated projections agree with the data, with the structure observed only through the imaging operator. The deformation is computed via a gradient flow on a Lie group, and we derive the resulting framework in a general geometric setting before adapting it for single-particle cryo-electron microscopy. On synthetic data, we recover single- and multichain proteins and capture conformational transitions.
