RNAfbinv: an interactive Java application for fragment-based design of RNA sequences

Weinbrand, Lina; Avihoo, A.; Barash, Danny

doi:10.1093/bioinformatics/btt494

Cited by 16 publications

(29 citation statements)

References 17 publications

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“…However, sequence-based methods alone or with slight structure considerations have been exhausted for this task. Thus, we start from a structure-based approach and use our in-house inverse RNA folding program RNAfbinv [ 70 ] (available at http://www.cs.bgu.ac.il/~RNAexinv/RNAfbinv ) to transform the search task into sequence space. RNAfbinv receives as input a secondary structure along with sequence constraints, and outputs a set of designed sequences that are predicted to be consistent with the input structure.…”

Section: Methodsmentioning

confidence: 99%

“…A similar idea was used in [ 51 ] to identify IRES-like structural domains using the inverse folding algorithm RNAiFOLD [ 71 ]. The flexibility of RNAfbinv [ 70 ] opens new possibilities in sampling the search space that are not covered by any other method developed before because a few more or less nucleotides in certain fragments are allowed in the solution. A summary of the computational method for the RNA inverse folding solver we used and the ingredients for RNAfbinv are provided in the next sub-section.…”

Section: Methodsmentioning

confidence: 99%

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An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding

et al. 2015

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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is to find additional eukaryotic riboswitches since more than 20 riboswitch classes have been found in prokaryotes but only one class has been found in eukaryotes. Moreover, this single known class of eukaryotic riboswitch, namely the TPP riboswitch class, has been found in bacteria, archaea, fungi and plants but not in animals. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods such as a combination of BLAST and pattern matching techniques that incorporate base-pairing considerations. None of these approaches perform energy minimization structure predictions. There is a clear motivation to develop new bioinformatics methods, aside of the ongoing advances in covariance models, that will sample the sequence search space more flexibly using structural guidance while retaining the computational efficiency of sequence-based methods. We present a new energy minimization approach that transforms structure-based search into a sequence-based search, thereby enabling the utilization of well established sequence-based search utilities such as BLAST and FASTA. The transformation to sequence space is obtained by using an extended inverse RNA folding problem solver with sequence and structure constraints, available within RNAfbinv. Examples in applying the new method are presented for the purine and preQ1 riboswitches. The method is described in detail along with its findings in prokaryotes. Potential uses in finding novel eukaryotic riboswitches and optimizing pre-designed synthetic riboswitches based on ligand simulations are discussed. The method components are freely available for use.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding

et al. 2015

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“…To our knowledge, the only other web servers or software for RNA design are: ( 4 ), ( 3 ), ( 19 ), ( 6 ), ( 2 ), ( 1 ), (web server is called RNAdesigner) ( 20 ), ( 5 ), ( 14 ). Default parameters were used for all software, with the exception of , where we used flags .…”

Section: Comparison With Other Softwarementioning

confidence: 99%

RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules

2015

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Several algorithms for RNA inverse folding have been used to design synthetic riboswitches, ribozymes and thermoswitches, whose activity has been experimentally validated. The software is unique among approaches for inverse folding in that (exhaustive) constraint programming is used instead of heuristic methods. For that reason, can generate all sequences that fold into the target structure or determine that there is no solution. is a complete overhaul of , rewritten from the now defunct COMET language to C++. The new code properly extends the capabilities of its predecessor by providing a user-friendly pipeline to design synthetic constructs having the functionality of given Rfam families. In addition, the new software supports amino acid constraints, even for proteins translated in different reading frames from overlapping coding sequences; moreover, structure compatibility/incompatibility constraints have been expanded. With these features, allows the user to design single RNA molecules as well as hybridization complexes of two RNA molecules. Availability: the web server, source code and linux binaries are publicly accessible at http://bioinformatics.bc.edu/clotelab/RNAiFold2.0.

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“…5 A tree-graph illustration for a coarse grain representation [ 29 ] of RNA secondary structures this type of sequence design, put forth in [ 30 ], relies on programs from the Vienna RNA package such as RNAfold, RNAinverse, and RNAdistance [ 10 ]. This time, the user downloads a program called RNAfbinv [ 31 ] (RNA fragment-based design), runs the application, and in the input screen inserts a secondary structure as input in dot-bracket representation. Upon pressing "Fragment", a new window opens where the user can choose a fragment constraint using a combo-box to select a desired motif that should be preserved.…”

Section: Computational Rna Designmentioning

confidence: 99%

Free Energy Minimization to Predict RNA Secondary Structures and Computational RNA Design

Churkin

Weinbrand

Barash

2014

Methods in Molecular Biology

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Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

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RNAfbinv: an interactive Java application for fragment-based design of RNA sequences

Abstract: RNAfbinv is freely available for download on the web at http://www.cs.bgu.ac.il/~RNAexinv/RNAfbinv. The site contains a help file with an explanation regarding the exact use.

Cited by 16 publications

References 17 publications

An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding

An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding

RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules

Free Energy Minimization to Predict RNA Secondary Structures and Computational RNA Design

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