RNA 3D Structure Comparison Using RNA-Puzzles Toolkit

Overview

Journal Methods Mol Biol

Specialty Molecular Biology

Date 2023 Jan 27

PMID 36705910

Authors

Marcin Magnus

Zhichao Miao

Affiliations

Soon will be listed here.

Abstract

Computational modeling of RNA three-dimensional (3D) structure may help in unrevealing the molecular mechanisms of RNA molecules and in designing molecules with novel functions. An unbiased blind assessment to benchmark the computational modeling is required to understand the achievements and bottlenecks of the prediction, while a standard structure comparison protocol is necessary. RNA-Puzzles is a community-wide effort on the assessment of blind prediction of RNA tertiary structures. And RNA-Puzzles toolkit is a computational resource derived from RNA-Puzzles, which includes (i) decoy sets generated by different RNA 3D structure prediction methods; (ii) 3D structure normalization, analysis, manipulation, and visualization tools; and (iii) 3D structure comparison metric tools. In this chapter, we illustrate a standard RNA 3D structure prediction assessment protocol using the selected tools from RNA-Puzzles toolkit: rna-tools and RNA_assessment.

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References

Strobel E, Watters K, Loughrey D, Lucks J . RNA systems biology: uniting functional discoveries and structural tools to understand global roles of RNAs. Curr Opin Biotechnol. 2016; 39:182-191. PMC: 5098397. DOI: 10.1016/j.copbio.2016.03.019. View

Sharp P . The centrality of RNA. Cell. 2009; 136(4):577-80. DOI: 10.1016/j.cell.2009.02.007. View

Cech T, Steitz J . The noncoding RNA revolution-trashing old rules to forge new ones. Cell. 2014; 157(1):77-94. DOI: 10.1016/j.cell.2014.03.008. View

Long Y, Wang X, Youmans D, Cech T . How do lncRNAs regulate transcription?. Sci Adv. 2017; 3(9):eaao2110. PMC: 5617379. DOI: 10.1126/sciadv.aao2110. View

Buratti E, Baralle F . Influence of RNA secondary structure on the pre-mRNA splicing process. Mol Cell Biol. 2004; 24(24):10505-14. PMC: 533984. DOI: 10.1128/MCB.24.24.10505-10514.2004. View

Luco R, Misteli T . More than a splicing code: integrating the role of RNA, chromatin and non-coding RNA in alternative splicing regulation. Curr Opin Genet Dev. 2011; 21(4):366-72. PMC: 6317717. DOI: 10.1016/j.gde.2011.03.004. View

Valencia-Sanchez M, Liu J, Hannon G, Parker R . Control of translation and mRNA degradation by miRNAs and siRNAs. Genes Dev. 2006; 20(5):515-24. DOI: 10.1101/gad.1399806. View

Al-Hashimi H, Walter N . RNA dynamics: it is about time. Curr Opin Struct Biol. 2008; 18(3):321-9. PMC: 2580758. DOI: 10.1016/j.sbi.2008.04.004. View

Mustoe A, Brooks C, Al-Hashimi H . Hierarchy of RNA functional dynamics. Annu Rev Biochem. 2014; 83:441-66. PMC: 4048628. DOI: 10.1146/annurev-biochem-060713-035524. View

10.

Mustoe A, Busan S, Rice G, Hajdin C, Peterson B, Ruda V . Pervasive Regulatory Functions of mRNA Structure Revealed by High-Resolution SHAPE Probing. Cell. 2018; 173(1):181-195.e18. PMC: 5866243. DOI: 10.1016/j.cell.2018.02.034. View

11.

Levitt M . Detailed molecular model for transfer ribonucleic acid. Nature. 1969; 224(5221):759-63. DOI: 10.1038/224759a0. View

12.

Rother M, Rother K, Puton T, Bujnicki J . ModeRNA: a tool for comparative modeling of RNA 3D structure. Nucleic Acids Res. 2011; 39(10):4007-22. PMC: 3105415. DOI: 10.1093/nar/gkq1320. View

13.

Popenda M, Szachniuk M, Antczak M, Purzycka K, Lukasiak P, Bartol N . Automated 3D structure composition for large RNAs. Nucleic Acids Res. 2012; 40(14):e112. PMC: 3413140. DOI: 10.1093/nar/gks339. View

14.

Zhao Y, Huang Y, Gong Z, Wang Y, Man J, Xiao Y . Automated and fast building of three-dimensional RNA structures. Sci Rep. 2012; 2:734. PMC: 3471093. DOI: 10.1038/srep00734. View

15.

Xu X, Zhao C, Chen S . VfoldLA: A web server for loop assembly-based prediction of putative 3D RNA structures. J Struct Biol. 2019; 207(3):235-240. PMC: 6711797. DOI: 10.1016/j.jsb.2019.06.002. View

16.

Jonikas M, Radmer R, Laederach A, Das R, Pearlman S, Herschlag D . Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters. RNA. 2009; 15(2):189-99. PMC: 2648710. DOI: 10.1261/rna.1270809. View

17.

Sharma S, Ding F, Dokholyan N . iFoldRNA: three-dimensional RNA structure prediction and folding. Bioinformatics. 2008; 24(17):1951-2. PMC: 2559968. DOI: 10.1093/bioinformatics/btn328. View

18.

Krokhotin A, Houlihan K, Dokholyan N . iFoldRNA v2: folding RNA with constraints. Bioinformatics. 2015; 31(17):2891-3. PMC: 4547609. DOI: 10.1093/bioinformatics/btv221. View

19.

Boniecki M, Lach G, Dawson W, Tomala K, Lukasz P, Soltysinski T . SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction. Nucleic Acids Res. 2015; 44(7):e63. PMC: 4838351. DOI: 10.1093/nar/gkv1479. View

20.

Parisien M, Cruz J, Westhof E, Major F . New metrics for comparing and assessing discrepancies between RNA 3D structures and models. RNA. 2009; 15(10):1875-85. PMC: 2743038. DOI: 10.1261/rna.1700409. View