Predicting RNA structure: advances and limitations.

RNA secondary structures can be predicted using efficient algorithms. A widely used software package implementing a large number of computational methods is the ViennaRNA Package. This chapter describes how to use programs from the ViennaRNA Package to perform common tasks such as prediction of minimum free-energy structures, suboptimal structures, or base pairing probabilities, and generating secondary structure plots with reliability annotation. Moreover, we present recent methods to assess the folding kinetics of an RNA via 2D projections of the energy landscape, identification of local minima and energy barriers, or simulation of RNA folding as a Markov process.

[1]  Ronny Lorenz,et al.  The Vienna RNA Websuite , 2008, Nucleic Acids Res..

[2]  Peter F. Stadler,et al.  ViennaRNA Package 2.0 , 2011, Algorithms for Molecular Biology.

[3]  Michael T. Wolfinger,et al.  Barrier Trees of Degenerate Landscapes , 2002 .

[4]  Michael Zuker,et al.  Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information , 1981, Nucleic Acids Res..

[5]  D. Baker,et al.  Atomic accuracy in predicting and designing non-canonical RNA structure , 2010, Nature Methods.

[6]  Jérôme Waldispühl,et al.  Towards 3D structure prediction of large RNA molecules: an integer programming framework to insert local 3D motifs in RNA secondary structure , 2012, Bioinform..

[7]  D. Turner,et al.  Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[8]  J. Sabina,et al.  Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. , 1999, Journal of molecular biology.

[9]  P. Schuster,et al.  Complete suboptimal folding of RNA and the stability of secondary structures. , 1999, Biopolymers.

[10]  Michael T. Wolfinger,et al.  Efficient computation of RNA folding dynamics , 2004 .

[11]  Ronny Lorenz,et al.  2D Projections of RNA Folding Landscapes , 2009, GCB.

[12]  Kevin P. Murphy,et al.  Efficient parameter estimation for RNA secondary structure prediction , 2007, ISMB/ECCB.

[13]  Jerrold R. Griggs,et al.  Algorithms for Loop Matchings , 1978 .

[14]  J. McCaskill The equilibrium partition function and base pair binding probabilities for RNA secondary structure , 1990, Biopolymers.

[15]  M. Zuker On finding all suboptimal foldings of an RNA molecule. , 1989, Science.

[16]  C. Lawrence,et al.  A statistical sampling algorithm for RNA secondary structure prediction. , 2003, Nucleic acids research.

[17]  Jamie J. Cannone,et al.  Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction , 2004, BMC Bioinformatics.