GaussianEM: Model compositional and conformational heterogeneity using 3D Gaussians

Understanding protein flexibility and its dynamic interactions with other molecules is essential for protein function study. Cryogenic electron microscopy (cryo-EM) provides an opportunity to directly observe macromolecular dynamics. However, analyzing datasets that contain both continuous motions and discrete states remains highly challenging. Here we present GaussianEM, a Gaussian pseudo-atomic framework that simultaneously models compositional and conformational heterogeneity from experimental cryo-EM images. GaussianEM employs a two-encoder-one-decoder architecture to map an image to its individual Gaussian components, and represent structural variability through changes in Gaussian parameters. This approach provides an intuitive and interpretable description of conformational changes, preserves local structural consistency along the transition trajectories, and naturally bridges the gap between density-based models and corresponding atomic models. We demonstrate the effectiveness of GaussianEM on both simulated and experimental datasets.

CryoAlign: feature-based method for global and local 3D alignment of EM density maps

Advances on cryo-electron imaging technologies have led to a rapidly increasing number of density maps. Alignment and comparison of density maps play a crucial role in interpreting structural information, such as conformational heterogeneity analysis using global alignment and atomic model assembly through local alignment. Here, we propose a fast and accurate global and local cryo-electron microscopy density map alignment method CryoAlign, which leverages local density feature descriptors to capture spatial structure similarities. CryoAlign is the first feature-based EM map alignment tool, in which the employment of feature-based architecture enables the rapid establishment of point pair correspondences and robust estimation of alignment parameters. Extensive experimental evaluations demonstrate the superiority of CryoAlign over the existing methods in both alignment accuracy and speed.