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Cryo-electron microscopy (cryo-EM) single-particle reconstruction is challenged by molecular flexibility and unknown imaging poses when resolving heterogeneous conformations. We propose CryoHCT, a Transformer-based encoder-decoder framework for ab initio heterogeneous reconstruction without pose priors. By integrating a conformation Transformer with an implicit neural decoder, CryoHCT achieved mean pose errors of 2.0° (IgG-1D) and 1.9° (Spike-MD), outperformed amortized inference baselines. Fourier Shell Correlation (FSC at 0.5 threshold) resolutions of 11.79 Å and 6.50 Å confirm high-fidelity recovery of continuous dynamics (e.g., Fab rotation). The method bridges pose diversity exploration with conformational continuity, offering a scalable solution for dynamic biomolecule analysis.

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Improving Heterogeneous Cryo-EM Reconstruction Using Transformer Architecture

  • 会议论文

  • 发表日期：

    2025年

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  • Jianquan Ouyang,
  • Xin Liu,
  • Qiaoxuan Yin

摘要

Cryo-electron microscopy (cryo-EM) single-particle reconstruction is challenged by molecular flexibility and unknown imaging poses when resolving heterogeneous conformations. We propose CryoHCT, a Transformer-based encoder-decoder framework for ab initio heterogeneous reconstruction without pose priors. By integrating a conformation Transformer with an implicit neural decoder, CryoHCT achieved mean pose errors of 2.0° (IgG-1D) and 1.9° (Spike-MD), outperformed amortized inference baselines. Fourier Shell Correlation (FSC at 0.5 threshold) resolutions of 11.79 Å and 6.50 Å confirm high-fidelity recovery of continuous dynamics (e.g., Fab rotation). The method bridges pose diversity exploration with conformational continuity, offering a scalable solution for dynamic biomolecule analysis.