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Automated model building and protein identification in cryo-EM maps

Author

Listed:
  • Kiarash Jamali

    (MRC Laboratory of Molecular Biology)

  • Lukas Käll

    (KTH Royal Institute of Technology)

  • Rui Zhang

    (Washington University in St Louis)

  • Alan Brown

    (Harvard Medical School)

  • Dari Kimanius

    (MRC Laboratory of Molecular Biology)

  • Sjors H. W. Scheres

    (MRC Laboratory of Molecular Biology)

Abstract

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination.

Suggested Citation

  • Kiarash Jamali & Lukas Käll & Rui Zhang & Alan Brown & Dari Kimanius & Sjors H. W. Scheres, 2024. "Automated model building and protein identification in cryo-EM maps," Nature, Nature, vol. 628(8007), pages 450-457, April.
  • Handle: RePEc:nat:nature:v:628:y:2024:i:8007:d:10.1038_s41586-024-07215-4
    DOI: 10.1038/s41586-024-07215-4
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    Cited by:

    1. Tao Li & Hong Cao & Jiahua He & Sheng-You Huang, 2024. "Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Bozhidar S. Ivanov & Hannah R. Bridges & Owen D. Jarman & Judy Hirst, 2024. "Structure of the turnover-ready state of an ancestral respiratory complex I," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    3. Hyunwook Lee & Ruben Assaraf & Suriyasri Subramanian & Dan Goetschius & Jan Bieri & Nadia M. DiNunno & Remo Leisi & Carol M. Bator & Susan L. Hafenstein & Carlos Ros, 2024. "Infectious parvovirus B19 circulates in the blood coated with active host protease inhibitors," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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