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

Zhichao Miao, Ryszard W. Adamiak, Marc Frédérick Blanchet, Michal Boniecki, Janusz M. Bujnicki, Shi Jie Chen, Clarence Cheng, Grzegorz Chojnowski, Fang Chieh Chou, Pablo Cordero, José Almeida Cruz, Adrian R. Ferré-D'Amaré, Rhiju Das, Feng Ding, Nikolay V. Dokholyan, Stanislaw Dunin-Horkawicz, Wipapat Kladwang, Andrey Krokhotin, Grzegorz Lach, Marcin MagnusFrançois Major, Thomas H. Mann, Benoît Masquida, Dorota Matelska, Mélanie Meyer, Alla Peselis, Mariusz Popenda, Katarzyna J. Purzycka, Alexander Serganov, Juliusz Stasiewicz, Marta Szachniuk, Arpit Tandon, Siqi Tian, Jian Wang, Yi Xiao, Xiaojun Xu, Jinwei Zhang, Peinan Zhao, Tomasz Zok, Eric Westhof

Research output: Contribution to journalArticle

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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/.

Original languageEnglish (US)
Pages (from-to)1066-1084
Number of pages19
JournalRNA (New York, N.Y.)
Volume21
Issue number6
DOIs
StatePublished - Jun 1 2015

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RNA
Riboswitch
RNA Folding
Catalytic RNA
Transfer RNA
RNA primers

All Science Journal Classification (ASJC) codes

  • Molecular Biology

Cite this

Miao, Z., Adamiak, R. W., Blanchet, M. F., Boniecki, M., Bujnicki, J. M., Chen, S. J., ... Westhof, E. (2015). RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures. RNA (New York, N.Y.), 21(6), 1066-1084. https://doi.org/10.1261/rna.049502.114
Miao, Zhichao ; Adamiak, Ryszard W. ; Blanchet, Marc Frédérick ; Boniecki, Michal ; Bujnicki, Janusz M. ; Chen, Shi Jie ; Cheng, Clarence ; Chojnowski, Grzegorz ; Chou, Fang Chieh ; Cordero, Pablo ; Cruz, José Almeida ; Ferré-D'Amaré, Adrian R. ; Das, Rhiju ; Ding, Feng ; Dokholyan, Nikolay V. ; Dunin-Horkawicz, Stanislaw ; Kladwang, Wipapat ; Krokhotin, Andrey ; Lach, Grzegorz ; Magnus, Marcin ; Major, François ; Mann, Thomas H. ; Masquida, Benoît ; Matelska, Dorota ; Meyer, Mélanie ; Peselis, Alla ; Popenda, Mariusz ; Purzycka, Katarzyna J. ; Serganov, Alexander ; Stasiewicz, Juliusz ; Szachniuk, Marta ; Tandon, Arpit ; Tian, Siqi ; Wang, Jian ; Xiao, Yi ; Xu, Xiaojun ; Zhang, Jinwei ; Zhao, Peinan ; Zok, Tomasz ; Westhof, Eric. / RNA-Puzzles Round II : assessment of RNA structure prediction programs applied to three large RNA structures. In: RNA (New York, N.Y.). 2015 ; Vol. 21, No. 6. pp. 1066-1084.
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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 {\AA}, 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/.",
author = "Zhichao Miao and Adamiak, {Ryszard W.} and Blanchet, {Marc Fr{\'e}d{\'e}rick} and Michal Boniecki and Bujnicki, {Janusz M.} and Chen, {Shi Jie} and Clarence Cheng and Grzegorz Chojnowski and Chou, {Fang Chieh} and Pablo Cordero and Cruz, {Jos{\'e} Almeida} and Ferr{\'e}-D'Amar{\'e}, {Adrian R.} and Rhiju Das and Feng Ding and Dokholyan, {Nikolay V.} and Stanislaw Dunin-Horkawicz and Wipapat Kladwang and Andrey Krokhotin and Grzegorz Lach and Marcin Magnus and Fran{\cc}ois Major and Mann, {Thomas H.} and Beno{\^i}t Masquida and Dorota Matelska and M{\'e}lanie Meyer and Alla Peselis and Mariusz Popenda and Purzycka, {Katarzyna J.} and Alexander Serganov and Juliusz Stasiewicz and Marta Szachniuk and Arpit Tandon and Siqi Tian and Jian Wang and Yi Xiao and Xiaojun Xu and Jinwei Zhang and Peinan Zhao and Tomasz Zok and Eric Westhof",
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Miao, Z, Adamiak, RW, Blanchet, MF, Boniecki, M, Bujnicki, JM, Chen, SJ, Cheng, C, Chojnowski, G, Chou, FC, Cordero, P, Cruz, JA, Ferré-D'Amaré, AR, Das, R, Ding, F, Dokholyan, NV, Dunin-Horkawicz, S, Kladwang, W, Krokhotin, A, Lach, G, Magnus, M, Major, F, Mann, TH, Masquida, B, Matelska, D, Meyer, M, Peselis, A, Popenda, M, Purzycka, KJ, Serganov, A, Stasiewicz, J, Szachniuk, M, Tandon, A, Tian, S, Wang, J, Xiao, Y, Xu, X, Zhang, J, Zhao, P, Zok, T & Westhof, E 2015, 'RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures', RNA (New York, N.Y.), vol. 21, no. 6, pp. 1066-1084. https://doi.org/10.1261/rna.049502.114

RNA-Puzzles Round II : assessment of RNA structure prediction programs applied to three large RNA structures. / Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric.

In: RNA (New York, N.Y.), Vol. 21, No. 6, 01.06.2015, p. 1066-1084.

Research output: Contribution to journalArticle

TY - JOUR

T1 - RNA-Puzzles Round II

T2 - assessment of RNA structure prediction programs applied to three large RNA structures

AU - Miao, Zhichao

AU - Adamiak, Ryszard W.

AU - Blanchet, Marc Frédérick

AU - Boniecki, Michal

AU - Bujnicki, Janusz M.

AU - Chen, Shi Jie

AU - Cheng, Clarence

AU - Chojnowski, Grzegorz

AU - Chou, Fang Chieh

AU - Cordero, Pablo

AU - Cruz, José Almeida

AU - Ferré-D'Amaré, Adrian R.

AU - Das, Rhiju

AU - Ding, Feng

AU - Dokholyan, Nikolay V.

AU - Dunin-Horkawicz, Stanislaw

AU - Kladwang, Wipapat

AU - Krokhotin, Andrey

AU - Lach, Grzegorz

AU - Magnus, Marcin

AU - Major, François

AU - Mann, Thomas H.

AU - Masquida, Benoît

AU - Matelska, Dorota

AU - Meyer, Mélanie

AU - Peselis, Alla

AU - Popenda, Mariusz

AU - Purzycka, Katarzyna J.

AU - Serganov, Alexander

AU - Stasiewicz, Juliusz

AU - Szachniuk, Marta

AU - Tandon, Arpit

AU - Tian, Siqi

AU - Wang, Jian

AU - Xiao, Yi

AU - Xu, Xiaojun

AU - Zhang, Jinwei

AU - Zhao, Peinan

AU - Zok, Tomasz

AU - Westhof, Eric

PY - 2015/6/1

Y1 - 2015/6/1

N2 - 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/.

AB - 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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DO - 10.1261/rna.049502.114

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