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International Conference on Research in Computational Molecular Biology

RECOMB 2015: Research in Computational Molecular Biology pp 80–95Cite as

KGSrna: Efficient 3D Kinematics-Based Sampling for Nucleic Acids

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9029))

Abstract

Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.

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Authors and Affiliations

  1. INRIA Saclay Ile de France, Campus de L’École Polytechnique, 1 Rue Honoré D’Estienne d’Orves, Bâtiment Alan Turing, 91120, Palaiseau, France

    Rasmus Fonseca & Julie Bernauer

  2. Laboratoire D’Informatique de L’École Polytechnique (LIX), CNRS UMR 7161, École Polytechnique, 91120, Palaiseau, France

    Rasmus Fonseca & Julie Bernauer

  3. Department of Computer Science, University of Copenhagen, Nørre Campus, Universitetsparken 5, 2100, Copenhagen, Denmark

    Rasmus Fonseca

  4. Joint Center for Structural Genomics, Stanford Synchrotron Radiation Lightsource, Stanford University, 2575 Sand Hill Road, Menlo Park, CA, 94025, USA

    Henry van den Bedem

Authors
  1. Rasmus Fonseca
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  2. Henry van den Bedem
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  3. Julie Bernauer
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Corresponding author

Correspondence to Rasmus Fonseca .

Editor information

Editors and Affiliations

  1. National Center of Biotechnology Information, Bethesda, Maryland, USA

    Teresa M. Przytycka

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Fonseca, R., van den Bedem, H., Bernauer, J. (2015). KGSrna: Efficient 3D Kinematics-Based Sampling for Nucleic Acids. In: Przytycka, T. (eds) Research in Computational Molecular Biology. RECOMB 2015. Lecture Notes in Computer Science(), vol 9029. Springer, Cham. https://doi.org/10.1007/978-3-319-16706-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-16706-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16705-3

  • Online ISBN: 978-3-319-16706-0

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