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Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps

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  • Tao Li

    (Huazhong University of Science and Technology)

  • Hong Cao

    (Huazhong University of Science and Technology)

  • Jiahua He

    (Huazhong University of Science and Technology)

  • Sheng-You Huang

    (Huazhong University of Science and Technology)

Abstract

Cryo-electron microscopy (cryo-EM) is one of the most powerful experimental methods for macromolecular structure determination. However, accurate DNA/RNA structure modeling from cryo-EM maps is still challenging especially for protein-DNA/RNA or multi-chain DNA/RNA complexes. Here we propose a deep learning-based method for accurate de novo structure determination of DNA/RNA from cryo-EM maps at

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53721-4
    DOI: 10.1038/s41467-024-53721-4
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    References listed on IDEAS

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    1. Zhaoming Su & Kaiming Zhang & Kalli Kappel & Shanshan Li & Michael Z. Palo & Grigore D. Pintilie & Ramya Rangan & Bingnan Luo & Yuquan Wei & Rhiju Das & Wah Chiu, 2021. "Cryo-EM structures of full-length Tetrahymena ribozyme at 3.1 Å resolution," Nature, Nature, vol. 596(7873), pages 603-607, August.
    2. Jiahua He & Peicong Lin & Ji Chen & Hong Cao & Sheng-You Huang, 2022. "Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    3. 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.
    4. Basil J. Greber & Daniel Boehringer & Alexander Leitner & Philipp Bieri & Felix Voigts-Hoffmann & Jan P. Erzberger & Marc Leibundgut & Ruedi Aebersold & Nenad Ban, 2014. "Architecture of the large subunit of the mammalian mitochondrial ribosome," Nature, Nature, vol. 505(7484), pages 515-519, January.
    5. Jiahua He & Tao Li & Sheng-You Huang, 2023. "Improvement of cryo-EM maps by simultaneous local and non-local deep learning," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    6. Genki Terashi & Daisuke Kihara, 2018. "De novo main-chain modeling for EM maps using MAINMAST," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
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