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Undesignable RNA Structure Identification via Rival Structure Generation and Structure Decomposition

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Research in Computational Molecular Biology (RECOMB 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14758))

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Abstract

RNA design is the search for a sequence or set of sequences that will fold into predefined structures, also known as the inverse problem of RNA folding. While numerous RNA design methods have been invented to find sequences capable of folding into a target structure, little attention has been given to the identification of undesignable structures according to the minimum free energy (\(\textrm{MFE}\)) criterion under the Turner model. In this paper, we address this gap by first introducing mathematical theorems outlining sufficient conditions for recognizing undesignable structures, then proposing efficient algorithms, guided by these theorems, to verify the undesignability of RNA structures. Through the application of these theorems and algorithms to the Eterna100 puzzles, we demonstrate the ability to efficiently establish that 15 of the puzzles indeed fall within the category of undesignable structures. In addition, we provide specific insights from the study of undesignability, in the hope that it will enable more understanding of RNA folding and RNA design.

Availability: Our source code is available at https://github.com/shanry/RNA-Undesign.

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Notes

  1. 1.

    We released those rival structures at https://github.com/shanry/RNA-Undesign/tree/main/data/results/rigend.

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Authors and Affiliations

  1. School of EECS, Oregon State University, Corvallis, OR, 97330, USA

    Tianshuo Zhou, Wei Yu Tang & Liang Huang

  2. Department of Biochemistry and Biophysics, Oregon State University, Corvallis, OR, 97330, USA

    Liang Huang

  3. Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY, 14642, USA

    David H. Mathews

  4. Center for RNA Biology, University of Rochester Medical Center, Rochester, NY, 14642, USA

    David H. Mathews

  5. Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, 14642, USA

    David H. Mathews

Authors
  1. Tianshuo Zhou
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  2. Wei Yu Tang
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  3. David H. Mathews
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  4. Liang Huang
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Corresponding author

Correspondence to Liang Huang .

Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Jian Ma

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Zhou, T., Tang, W.Y., Mathews, D.H., Huang, L. (2024). Undesignable RNA Structure Identification via Rival Structure Generation and Structure Decomposition. In: Ma, J. (eds) Research in Computational Molecular Biology. RECOMB 2024. Lecture Notes in Computer Science, vol 14758. Springer, Cham. https://doi.org/10.1007/978-1-0716-3989-4_17

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  • DOI: https://doi.org/10.1007/978-1-0716-3989-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-1-0716-3988-7

  • Online ISBN: 978-1-0716-3989-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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