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trRosettaRNA: automated prediction of RNA 3D structure with transformer network

Author

Listed:
  • Wenkai Wang

    (Nankai University)

  • Chenjie Feng

    (Shandong University
    Ningxia Medical University)

  • Renmin Han

    (Shandong University)

  • Ziyi Wang

    (Shandong University)

  • Lisha Ye

    (Nankai University)

  • Zongyang Du

    (Nankai University)

  • Hong Wei

    (Nankai University)

  • Fa Zhang

    (Beijing Institute of Technology)

  • Zhenling Peng

    (Shandong University)

  • Jianyi Yang

    (Shandong University)

Abstract

RNA 3D structure prediction is a long-standing challenge. Inspired by the recent breakthrough in protein structure prediction, we developed trRosettaRNA, an automated deep learning-based approach to RNA 3D structure prediction. The trRosettaRNA pipeline comprises two major steps: 1D and 2D geometries prediction by a transformer network; and 3D structure folding by energy minimization. Benchmark tests suggest that trRosettaRNA outperforms traditional automated methods. In the blind tests of the 15th Critical Assessment of Structure Prediction (CASP15) and the RNA-Puzzles experiments, the automated trRosettaRNA predictions for the natural RNAs are competitive with the top human predictions. trRosettaRNA also outperforms other deep learning-based methods in CASP15 when measured by the Z-score of the Root-Mean-Square Deviation. Nevertheless, it remains challenging to predict accurate structures for synthetic RNAs with an automated approach. We hope this work could be a good start toward solving the hard problem of RNA structure prediction with deep learning.

Suggested Citation

  • Wenkai Wang & Chenjie Feng & Renmin Han & Ziyi Wang & Lisha Ye & Zongyang Du & Hong Wei & Fa Zhang & Zhenling Peng & Jianyi Yang, 2023. "trRosettaRNA: automated prediction of RNA 3D structure with transformer network," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42528-4
    DOI: 10.1038/s41467-023-42528-4
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    1. Kathryn Tunyasuvunakool & Jonas Adler & Zachary Wu & Tim Green & Michal Zielinski & Augustin Žídek & Alex Bridgland & Andrew Cowie & Clemens Meyer & Agata Laydon & Sameer Velankar & Gerard J. Kleywegt, 2021. "Highly accurate protein structure prediction for the human proteome," Nature, Nature, vol. 596(7873), pages 590-596, August.
    2. Jaswinder Singh & Jack Hanson & Kuldip Paliwal & Yaoqi Zhou, 2019. "RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    3. Blake A. Sweeney & David Hoksza & Eric P. Nawrocki & Carlos Eduardo Ribas & Fábio Madeira & Jamie J. Cannone & Robin Gutell & Aparna Maddala & Caeden D. Meade & Loren Dean Williams & Anton S. Petrov &, 2021. "R2DT is a framework for predicting and visualising RNA secondary structure using templates," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    4. John Jumper & Richard Evans & Alexander Pritzel & Tim Green & Michael Figurnov & Olaf Ronneberger & Kathryn Tunyasuvunakool & Russ Bates & Augustin Žídek & Anna Potapenko & Alex Bridgland & Clemens Me, 2021. "Highly accurate protein structure prediction with AlphaFold," Nature, Nature, vol. 596(7873), pages 583-589, August.
    5. Marc Parisien & François Major, 2008. "The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data," Nature, Nature, vol. 452(7183), pages 51-55, March.
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