RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures
- Zhichao Miao1,
- Ryszard W. Adamiak2,
- Marc-Frédérick Blanchet3,
- Michal Boniecki4,
- Janusz M. Bujnicki4,5,
- Shi-Jie Chen6,
- Clarence Cheng7,
- Grzegorz Chojnowski4,
- Fang-Chieh Chou7,
- Pablo Cordero7,
- José Almeida Cruz1,
- Adrian R. Ferré-D'Amaré8,
- Rhiju Das7,
- Feng Ding9,
- Nikolay V. Dokholyan10,
- Stanislaw Dunin-Horkawicz4,
- Wipapat Kladwang7,
- Andrey Krokhotin10,
- Grzegorz Lach4,
- Marcin Magnus4,
- François Major3,
- Thomas H. Mann7,
- Benoît Masquida11,
- Dorota Matelska4,
- Mélanie Meyer12,
- Alla Peselis13,
- Mariusz Popenda2,
- Katarzyna J. Purzycka2,
- Alexander Serganov13,
- Juliusz Stasiewicz4,
- Marta Szachniuk14,
- Arpit Tandon10,
- Siqi Tian7,
- Jian Wang15,
- Yi Xiao15,
- Xiaojun Xu6,
- Jinwei Zhang8,
- Peinan Zhao6,
- Tomasz Zok14 and
- Eric Westhof1
- 1Architecture et Réactivité de l'ARN, Université de Strasbourg, Institut de biologie moléculaire et cellulaire du CNRS, 67000 Strasbourg, France
- 2Department of Structural Chemistry and Biology of Nucleic Acids, Structural Chemistry of Nucleic Acids Laboratory, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
- 3Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec, Canada H3C 3J7
- 4Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
- 5Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
- 6Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
- 7Department of Physics, Stanford University, Stanford, California 94305, USA
- 8National Heart, Lung and Blood Institute, Bethesda, Maryland 20892-8012, USA
- 9Department of Physics and Astronomy, College of Engineering and Science, Clemson University, Clemson, South Carolina 29634, USA
- 10Department of Biochemistry and Biophysics, University of North Carolina, School of Medicine, Chapel Hill, North Carolina 27599, USA
- 11Génétique Moléculaire Génomique Microbiologie, Institut de physiologie et de la chimie biologique, 67084 Strasbourg, France
- 12Institut de génétique et de biologie moléculaire et cellulaire, 67400 Strasbourg, France
- 13Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, New York 10016, USA
- 14Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
- 15Department of Physics, Huazhong University of Science and Technology, 430074 Wuhan, China
- Corresponding author: e.westhof{at}ibmc-cnrs.unistra.fr
Abstract
This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/.
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Footnotes
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Article published online ahead of print. Article and publication date are at http://www.rnajournal.org/cgi/doi/10.1261/rna.049502.114.
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Freely available online through the RNA Open Access option.
- Received January 10, 2015.
- Accepted February 12, 2015.
This article, published in RNA, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.