Automated and fast building of three-dimensional RNA structures

Zhao, Yunjie; Huang, Yangyu; Gong, Zhou; Wang, Yanjie; Man, Jianfen; Xiao, Yi

doi:10.1038/srep00734

Cited by 194 publications

(172 citation statements)

References 30 publications

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“…In each case, Mfold (Zuker et al 1999) was used to predict 2D structure and 3dRNA (Zhao et al 2012) to predict 3D structures of the given sequence, without using any experimental data. The 2D structures used were "….. ((((..(((….…”

Section: Xiao Groupmentioning

confidence: 99%

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme

Miao

Adamiak

Antczak

et al. 2017

RNA

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185

209

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RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5 ′ -triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homologyderived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson-Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.ustrasbg.fr/rnapuzzles/.

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Section: Xiao Groupmentioning

confidence: 99%

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme

Miao

Adamiak

Antczak

et al. 2017

RNA

Self Cite

185

209

View full text Add to dashboard Cite

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“…We have built the STAT3 protein model using protein structure and function prediction program, I-TASSER. 20 The DNA-protein complex structures have been constructed by 3dRNA 21 and 3dRPC 22 programs that are designed for structural modeling and docking of nucleic acid structures. While the two NDs within a P-STAT dimer are separated and do not interact with each other, 23 the NDs of two P-STAT dimers can interact to form a tetramer.…”

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confidence: 99%

A new role for STAT3 as a regulator of chromatin topology

et al. 2013

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“…Recently, we introduced a novel method for automated building of RNA tertiary structures based on RNA sequence and secondary structure [49]: 3dRNA (//122.205.6.127/ 3dRNA/3dRNA.html). As the tertiary structures of RNAs are restrained to a large extent by their secondary structures, we used a hierarchical approach.…”

Section: Rna Secondary Structure Predictionmentioning

confidence: 99%

“…One structure is a 27-nt pseudoknot with a prediction accuracy of 3.46 Å RMSD, while the other is an L-type tRNA structure with a prediction accuracy of 3.80 Å RMSD. We also compared 3dRNA with existing RNA tertiary structure prediction methods (FARNA, RNA2D3D, iFoldRNA, V-Fold, and MC-Sym) [49]. As the FARNA and V-fold servers were unavailable, the prediction results from the papers describing FARNA and V-fold were used for comparison (Table 1) [49].…”

Section: Rna Secondary Structure Predictionmentioning

confidence: 99%

“…We also compared 3dRNA with existing RNA tertiary structure prediction methods (FARNA, RNA2D3D, iFoldRNA, V-Fold, and MC-Sym) [49]. As the FARNA and V-fold servers were unavailable, the prediction results from the papers describing FARNA and V-fold were used for comparison (Table 1) [49]. The prediction accuracy of other methods (RNA2D3D, iFoldRNA, and MC-Sym) were calculated for a database of 185 RNAs built by us ( Table 2).…”

Section: Rna Secondary Structure Predictionmentioning

confidence: 99%

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Large-scale study of long non-coding RNA functions based on structure and expression features

Zhao

Wang

Chen

et al. 2013

Sci. China Life Sci.

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Mammals and other complex organisms can transcribe an abundance of long non-coding RNAs (lncRNAs) that fulfill a wide variety of regulatory roles in many biological processes. These roles, including as scaffolds and as guides for protein-coding genes, mainly depend on the structure and expression level of lncRNAs. In this review, we focus on the current methods for analyzing lncRNA structure and expression, which is basic but necessary information for in-depth, large-scale analysis of lncRNA functions. The ENCODE project, which has published 30 papers to date, including a few that extensively characterize long non-coding RNAs (lncRNAs), has revealed that 76% of the human genome is transcribed to produce a range of lncRNAs [1]. The landscape of lncRNAs in mammals was unveiled by the rapid progress of deep sequencing technology [2] and computational methods to identify lncRNA [3,4]. These lncRNAs participate in a wide variety of biological processes, such as imprinting control, cell differentiation, immune responses through regulating expression, and activity and localization of protein coding genes [5,6]. However, the function and mechanisms of most lncRNAs are still unknown. Here, we combine our work and other related work to systematically illustrate the current methods to study lncRNA function through their structures and expression profiles. RNA secondary structure predictionSecondary structures of RNAs are the basis of their tertiary structures, so we will first briefly review methods for their prediction. Such methods predict standard Watson-Crick base pairs (AU and CG) and non-standard base pairs in a RNA sequence. There are many methods for RNA secondary structure prediction, which are based on different principles. Here we focus on two types of commonly used methods: the minimum free energy method [7][8][9][10][11], and the multiple sequence alignment method [1214]. The minimum free energy methods are now the most widely used methods of RNA secondary structure predic-

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Automated and fast building of three-dimensional RNA structures

Cited by 194 publications

References 30 publications

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme

A new role for STAT3 as a regulator of chromatin topology

Large-scale study of long non-coding RNA functions based on structure and expression features

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