RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.
RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.
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DOI：
10.1261/rna.049502.114
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发表时间：
2015-06
期刊：
影响因子：
--
通讯作者：
Westhof E
中科院分区：
文献类型：
--
作者：
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
本文报道了第二轮RNA拼图，这是一项用于三维（3D） RNA结构预测的集体盲法实验。三个谜题，谜题5、谜题6和谜题10，代表了三个大的RNA结构序列，与之前解出的RNA分子有有限的同源性或没有同源性。7组使用RNAComposer、ModeRNA/SimRNA、Vfold、Rosetta、DMD、MC-Fold、3dRNA和AMBER精化预测了lariat-capping核酶以及与腺苷钴胺素和tRNA络合的核开关。一些小组使用最先进的化学制图方法（SHAPE、DMS、CMCT和mutate-and-map）的数据推导出模型。在衍射分辨率为2.5-3.2 Å的情况下，利用各种质量指标自动将预测结果与随后公布的三种晶体结构进行比较。这些比较清楚地表明了目前从头预测能力的状况以及这些最先进方法的局限性。所有最好的预测模型都具有与天然结构相似的拓扑结构，这表明RNA结构预测的计算方法已经可以为生物学问题提供有用的结构信息。然而，非watson - crick相互作用（rna正确折叠的关键）的预测精度较低，一些预测模型的Clash Scores很高。这两个困难指出了RNA结构预测的一些持续瓶颈。所有提交的模型都可以在。
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 .
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影响因子：
1.8
作者：
HOFACKER, IL;FONTANA, W;SCHUSTER, P
通讯作者：
SCHUSTER, P
影响因子：
14.9
作者：
Griffiths-Jones, S;Bateman, A;Eddy, SR
通讯作者：
Eddy, SR
影响因子：
4.5
作者：
Ding, Feng;Sharma, Shantanu;Dokholyan, Nikolay V.
通讯作者：
Dokholyan, Nikolay V.
DOI：
10.1073/pnas.1219988110
发表时间：
2013-04-02
影响因子：
11.1
作者：
Hajdin, Christine E.;Bellaousov, Stanislav;Weeks, Kevin M.
通讯作者：
Weeks, Kevin M.
预测RNA伪折叠热力学。
影响因子：
14.9
作者：
Cao, Song;Chen, Shi-Jie
通讯作者：
Chen, Shi-Jie