3DDF-VAE: Dual-frequency variational autoencoder with pose-consistency validation for rare cryo-EM conformation discovery.

Revealing the 3D conformational variability of biomolecules is crucial for understanding their function, while cryo-EM reconstruction of rare states remains difficult due to data imbalance and structural detail loss in existing generative models. We present a dual-stage pipeline consisting of a generative stage and a validation stage. In the generative stage, we employ a 3D dual-frequency variational autoencoder (3DDF-VAE) that separately models low- and high-frequency components of protein density maps to enhance global coherence and local structural detail. In the validation stage, a pose-consistency projection strategy evaluates the generated maps by comparison with the original 2D particles. Experiments on integrin αVβ8, T50S ribosome, and SARS-CoV-2 spike datasets demonstrate that our method produces high-quality density maps, identifies rare conformations, and reconstructs plausible intermediates, while ablation studies confirm the benefits of frequency separation and parameter optimization. This integrated generative-validation framework improves resolution, enhances rare conformation detection, and offers a data-driven approach to explore conformational heterogeneity in complex biomolecular systems.