2026Chen 3DDF-VAE

Citation

Chen, Y., Li, F., Dong, H., Wang, X., Zhang, F., Hu, B. and Wan, X. 2026. 3DDF-VAE: Dual-frequency variational autoencoder with pose-consistency validation for rare cryo-EM conformation discovery. J. Structural Biology. (2026), 108311.

Abstract

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.

Links

https://www.sciencedirect.com/science/article/pii/S1047847726000274