Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain.
The Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
Nat Commun. 2023 Jan 11;14(1):154. doi: 10.1038/s41467-023-35791-y.
The new developments in Cryo-EM Single Particle Analysis are helping us to understand how the macromolecular structure and function meet to drive biological processes. By capturing many states at the particle level, it is possible to address how macromolecules explore different conformations, information that is classically extracted through 3D classification. However, the limitations of classical approaches prevent us from fully understanding the complete conformational landscape due to the reduced number of discrete states accurately reconstructed. To characterize the whole structural spectrum of a macromolecule, we propose an extension of our Zernike3D approach, able to extract per-image continuous flexibility information directly from a particle dataset. Also, our method can be seamlessly applied to images, maps or atomic models, opening integrative possibilities. Furthermore, we introduce the ZART reconstruction algorithm, which considers the Zernike3D deformation fields to revert particle conformational changes during the reconstruction process, thus minimizing the blurring induced by molecular motions.
冷冻电镜单颗粒分析的新进展帮助我们了解大分子结构和功能如何相互作用以驱动生物过程。通过在颗粒水平上捕获许多状态，可以解决大分子如何探索不同构象的问题，这些信息通常是通过 3D 分类来提取的。然而，由于准确重建的离散状态数量减少，经典方法的局限性使得我们无法完全理解完整的构象景观。为了描述大分子的整个结构范围，我们提出了对我们的 Zernike3D 方法的扩展，该方法能够直接从粒子数据集提取每个图像的连续灵活性信息。此外，我们的方法可以无缝应用于图像、地图或原子模型，开辟了整合的可能性。此外，我们引入了 ZART 重建算法，该算法考虑了 Zernike3D 变形场，以在重建过程中反转粒子构象变化，从而最小化分子运动引起的模糊。
