Literature DB >> 28334976

A sensitivity analysis of RNA folding nearest neighbor parameters identifies a subset of free energy parameters with the greatest impact on RNA secondary structure prediction.

Jeffrey Zuber1, Hongying Sun1, Xiaoju Zhang1, Iain McFadyen2, David H Mathews1,3.   

Abstract

Nearest neighbor parameters for estimating the folding energy changes of RNA secondary structures are used in structure prediction and analysis. Despite their widespread application, a comprehensive analysis of the impact of each parameter on the precision of calculations had not been conducted. To identify the parameters with greatest impact, a sensitivity analysis was performed on the 291 parameters that compose the 2004 version of the free energy nearest neighbor rules. Perturbed parameter sets were generated by perturbing each parameter independently. Then the effect of each individual parameter change on predicted base-pair probabilities and secondary structures as compared to the standard parameter set was observed for a set of sequences including structured ncRNA, mRNA and randomized sequences. The results identify for the first time the parameters with the greatest impact on secondary structure prediction, and the subset which should be prioritized for further study in order to improve the precision of structure prediction. In particular, bulge loop initiation, multibranch loop initiation, AU/GU internal loop closure and AU/GU helix end parameters were particularly important. An analysis of parameter usage during folding free energy calculations of stochastic samples of secondary structures revealed a correlation between parameter usage and impact on structure prediction precision.
© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2017        PMID: 28334976      PMCID: PMC5449625          DOI: 10.1093/nar/gkx170

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  38 in total

1.  Thermodynamic parameters for an expanded nearest-neighbor model for the formation of RNA duplexes with single nucleotide bulges.

Authors:  Brent M Znosko; Sara B Silvestri; Heather Volkman; Bob Boswell; Martin J Serra
Journal:  Biochemistry       Date:  2002-08-20       Impact factor: 3.162

2.  A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

Authors:  Elena Rivas; Raymond Lang; Sean R Eddy
Journal:  RNA       Date:  2011-12-22       Impact factor: 4.942

3.  CONTRAfold: RNA secondary structure prediction without physics-based models.

Authors:  Chuong B Do; Daniel A Woods; Serafim Batzoglou
Journal:  Bioinformatics       Date:  2006-07-15       Impact factor: 6.937

4.  Prediction of alternative RNA secondary structures based on fluctuating thermodynamic parameters.

Authors:  S Y Le; J H Chen; J V Maizel
Journal:  Nucleic Acids Res       Date:  1993-05-11       Impact factor: 16.971

5.  The molecular mechanism of thermal unfolding of Escherichia coli formylmethionine transfer RNA.

Authors:  D M Crothers; P E Cole; C W Hilbers; R G Shulman
Journal:  J Mol Biol       Date:  1974-07-25       Impact factor: 5.469

Review 6.  RNA-guided isomerization of uridine to pseudouridine--pseudouridylation.

Authors:  Yi-Tao Yu; U Thomas Meier
Journal:  RNA Biol       Date:  2014       Impact factor: 4.652

7.  RNAstructure: software for RNA secondary structure prediction and analysis.

Authors:  Jessica S Reuter; David H Mathews
Journal:  BMC Bioinformatics       Date:  2010-03-15       Impact factor: 3.169

8.  ViennaRNA Package 2.0.

Authors:  Ronny Lorenz; Stephan H Bernhart; Christian Höner Zu Siederdissen; Hakim Tafer; Christoph Flamm; Peter F Stadler; Ivo L Hofacker
Journal:  Algorithms Mol Biol       Date:  2011-11-24       Impact factor: 1.405

9.  A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation.

Authors:  D M Layton; R Bundschuh
Journal:  Nucleic Acids Res       Date:  2005-01-26       Impact factor: 16.971

10.  uShuffle: a useful tool for shuffling biological sequences while preserving the k-let counts.

Authors:  Minghui Jiang; James Anderson; Joel Gillespie; Martin Mayne
Journal:  BMC Bioinformatics       Date:  2008-04-11       Impact factor: 3.169

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  11 in total

1.  Determining parameters for non-linear models of multi-loop free energy change.

Authors:  Max Ward; Hongying Sun; Amitava Datta; Michael Wise; David H Mathews
Journal:  Bioinformatics       Date:  2019-11-01       Impact factor: 6.937

2.  Conditioning and Robustness of RNA Boltzmann Sampling under Thermodynamic Parameter Perturbations.

Authors:  Emily Rogers; David Murrugarra; Christine Heitsch
Journal:  Biophys J       Date:  2017-06-16       Impact factor: 4.033

3.  Validation of the nearest-neighbor model for Watson-Crick self-complementary DNA duplexes in molecular crowding condition.

Authors:  Saptarshi Ghosh; Shuntaro Takahashi; Tamaki Endoh; Hisae Tateishi-Karimata; Soumitra Hazra; Naoki Sugimoto
Journal:  Nucleic Acids Res       Date:  2019-04-23       Impact factor: 16.971

Review 4.  How to benchmark RNA secondary structure prediction accuracy.

Authors:  David H Mathews
Journal:  Methods       Date:  2019-04-02       Impact factor: 3.608

5.  Vfold2D-MC: A Physics-Based Hybrid Model for Predicting RNA Secondary Structure Folding.

Authors:  Yi Cheng; Sicheng Zhang; Xiaojun Xu; Shi-Jie Chen
Journal:  J Phys Chem B       Date:  2021-09-02       Impact factor: 2.991

6.  PATTERNA: transcriptome-wide search for functional RNA elements via structural data signatures.

Authors:  Mirko Ledda; Sharon Aviran
Journal:  Genome Biol       Date:  2018-03-01       Impact factor: 13.583

7.  Analysis of RNA nearest neighbor parameters reveals interdependencies and quantifies the uncertainty in RNA secondary structure prediction.

Authors:  Jeffrey Zuber; B Joseph Cabral; Iain McFadyen; David M Mauger; David H Mathews
Journal:  RNA       Date:  2018-08-13       Impact factor: 4.942

Review 8.  Challenges and approaches to predicting RNA with multiple functional structures.

Authors:  Susan J Schroeder
Journal:  RNA       Date:  2018-08-24       Impact factor: 4.942

9.  Estimating uncertainty in predicted folding free energy changes of RNA secondary structures.

Authors:  Jeffrey Zuber; David H Mathews
Journal:  RNA       Date:  2019-04-05       Impact factor: 4.942

10.  LinearPartition: linear-time approximation of RNA folding partition function and base-pairing probabilities.

Authors:  He Zhang; Liang Zhang; David H Mathews; Liang Huang
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

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