RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

• DOI: 10.1261/rna.049502.114
• Publication Date: 2015-04-17T02:51:54Z
• Authors: Zhichao Miao; Ryszard W. Adamiak; Marc-Frédérick Bl...; Michal Boniecki; Janusz M. Bujnicki; Shi-Jie Chen; Clarence Cheng; Grzegorz Chojnowski; Fang-Chieh Chou; Pablo Cordero; José Almeida Cruz; Adrian R. Ferré-D...; Rhiju Das; Feng Ding; Nikolay V. Dokholyan; Stanislaw Dunin-H...; Wipapat Kladwang; Andrey Krokhotin; Grzegorz Lach; Marcin Magnus; François Major; Thomas H. Mann; Benoît Masquida; Dorota Matelska; Mélanie Meyer; Alla Peselis; Mariusz Popenda; Katarzyna J. Purz...; Alexander Serganov; Juliusz Stasiewicz; Marta Szachniuk; Arpit Tandon; Siqi Tian; Jian Wang; Yi Xiao; Xiaojun Xu; Jinwei Zhang; Peinan Zhao; Tomasz Zok; Eric Westhof
• Keywords: Models, Molecular; 0303 health sciences; 03 medical and health sciences; RNA, Transfer; Bioinformatics; Computational Biology; Nucleic Acid Conformation; RNA; RNA, Messenger; Crystallography, X-Ray; Software

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/.