INFO-RNA--a server for fast inverse RNA folding satisfying sequence constraints.
Ontology highlight
ABSTRACT:
SUBMITTER: Busch A
PROVIDER: S-EPMC1933236 | biostudies-literature | 2007 Jul
REPOSITORIES: biostudies-literature
Publications
INFO-RNA--a server for fast inverse RNA folding satisfying sequence constraints.
Nucleic acids research 20070422 Web Server issue
INFO-RNA is a new web server for designing RNA sequences that fold into a user given secondary structure. Furthermore, constraints on the sequence can be specified, e.g. one can restrict sequence positions to a fixed nucleotide or to a set of nucleotides. Moreover, the user can allow violations of the constraints at some positions, which can be advantageous in complicated cases. The INFO-RNA web server allows biologists to design RNA sequences in an automatic manner. It is clearly and intuitivel ...[more]
Similar Datasets
Project description:Synthetic biology and nanotechnology are poised to make revolutionary contributions to the 21st century. In this article, we describe a new web server to support in silico RNA molecular design. Given an input target RNA secondary structure, together with optional constraints, such as requiring GC-content to lie within a certain range, requiring the number of strong (GC), weak (AU) and wobble (GU) base pairs to lie in a certain range, the RNAiFold web server determines one or more RNA sequences, whose minimum free-energy secondary structure is the target structure. RNAiFold provides access to two servers: RNA-CPdesign, which applies constraint programming, and RNA-LNSdesign, which applies the large neighborhood search heuristic; hence, it is suitable for larger input structures. Both servers can also solve the RNA inverse hybridization problem, i.e. given a representation of the desired hybridization structure, RNAiFold returns two sequences, whose minimum free-energy hybridization is the input target structure. The web server is publicly accessible at http://bioinformatics.bc.edu/clotelab/RNAiFold, which provides access to two specialized servers: RNA-CPdesign and RNA-LNSdesign. Source code for the underlying algorithms, implemented in COMET and supported on linux, can be downloaded at the server website.
| S-EPMC3692061 | biostudies-literature
Project description:BackgroundRNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard.ResultsIn this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets.ConclusionsOur method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.
| S-EPMC3534541 | biostudies-literature
Project description:A key to understanding RNA function is to uncover its complex 3D structure. Experimental methods used for determining RNA 3D structures are technologically challenging and laborious, which makes the development of computational prediction methods of substantial interest. Previously, we developed the iFoldRNA server that allows accurate prediction of short (<50?nt) tertiary RNA structures starting from primary sequences. Here, we present a new version of the iFoldRNA server that permits the prediction of tertiary structure of RNAs as long as a few hundred nucleotides. This substantial increase in the server capacity is achieved by utilization of experimental information such as base-pairing and hydroxyl-radical probing. We demonstrate a significant benefit provided by integration of experimental data and computational methods.http://ifoldrna.dokhlab.orgdokh@unc.eu.
| S-EPMC4547609 | biostudies-literature
Project description:Artificially synthesized RNA molecules have recently come under study since such molecules have a potential for creating a variety of novel functional molecules. When designing artificial RNA sequences, secondary structure should be taken into account since functions of noncoding RNAs strongly depend on their structure. RNA inverse folding is a methodology for computationally exploring the RNA sequences folding into a user-given target structure. In the present study, we developed a multi-objective genetic algorithm, MODENA (Multi-Objective DEsign of Nucleic Acids), for RNA inverse folding. MODENA explores the approximate set of weak Pareto optimal solutions in the objective function space of 2 objective functions, a structure stability score and structure similarity score. MODENA can simultaneously design multiple different RNA sequences at 1 run, whose lowest free energies range from a very stable value to a higher value near those of natural counterparts. MODENA and previous RNA inverse folding programs were benchmarked with 29 target structures taken from the Rfam database, and we found that MODENA can successfully design 23 RNA sequences folding into the target structures; this result is better than those of the other benchmarked RNA inverse folding programs. The multi-objective genetic algorithm gives a useful framework for a functional biomolecular design. Executable files of MODENA can be obtained at http://rna.eit.hirosaki-u.ac.jp/modena/.
| S-EPMC3169953 | biostudies-literature
Project description:BackgroundMetal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects.ResultsThe TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects.ConclusionsBy accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.
| S-EPMC4370743 | biostudies-literature
Project description:Artificially synthesized RNA molecules provide important ways for creating a variety of novel functional molecules. State-of-the-art RNA inverse folding algorithms can design simple and short RNA sequences of specific GC content, that fold into the target RNA structure. However, their performance is not satisfactory in complicated cases.We present a new inverse folding algorithm called MCTS-RNA, which uses Monte Carlo tree search (MCTS), a technique that has shown exceptional performance in Computer Go recently, to represent and discover the essential part of the sequence space. To obtain high accuracy, initial sequences generated by MCTS are further improved by a series of local updates. Our algorithm has an ability to control the GC content precisely and can deal with pseudoknot structures. Using common benchmark datasets for evaluation, MCTS-RNA showed a lot of promise as a standard method of RNA inverse folding.MCTS-RNA is available at https://github.com/tsudalab/MCTS-RNA .
| S-EPMC5674771 | biostudies-literature
Project description:Computational programs for predicting RNA sequences with desired folding properties have been extensively developed and expanded in the past several years. Given a secondary structure, these programs aim to predict sequences that fold into a target minimum free energy secondary structure, while considering various constraints. This procedure is called inverse RNA folding. Inverse RNA folding has been traditionally used to design optimized RNAs with favorable properties, an application that is expected to grow considerably in the future in light of advances in the expanding new fields of synthetic biology and RNA nanostructures. Moreover, it was recently demonstrated that inverse RNA folding can successfully be used as a valuable preprocessing step in computational detection of novel noncoding RNAs. This review describes the most popular freeware programs that have been developed for such purposes, starting from RNAinverse that was devised when formulating the inverse RNA folding problem. The most recently published ones that consider RNA secondary structure as input are antaRNA, RNAiFold and incaRNAfbinv, each having different features that could be beneficial to specific biological problems in practice. The various programs also use distinct approaches, ranging from ant colony optimization to constraint programming, in addition to adaptive walk, simulated annealing and Boltzmann sampling. This review compares between the various programs and provides a simple description of the various possibilities that would benefit practitioners in selecting the most suitable program. It is geared for specific tasks requiring RNA design based on input secondary structure, with an outlook toward the future of RNA design programs.
| S-EPMC6018860 | biostudies-literature
Project description:Internal ribosome entry site (IRES) elements govern protein synthesis of mRNAs that bypass cap-dependent translation inhibition under stress conditions. Picornavirus IRES are cis-acting elements, organized in modular domains that recruit the ribosome to internal mRNA sites. The aim of this study was to retrieve short RNA sequences with the capacity to adopt RNA folding patterns conserved with IRES structural subdomains, likely corresponding to RNA modules. We have applied a new program, RNAiFold, an inverse folding algorithm that determines all sequences whose minimum free energy structure is identical to that of the structural domains of interest. Sequences differing by more than 1 nt were clustered. Then, BLASTing one randomly chosen sequence from each cluster of the RNAiFold output, we retrieved viral and cellular sequences among output hits. As a proof of principle, we present the data corresponding to a coding region of Drosophila melanogaster TAF6, a transcription factor-associated protein that contains a structural motif within its coding region potentially folding into an IRES-like subdomain. This RNA region shows a biased codon usage, as predicted from structural constraints at the RNA level, it harbors conserved IRES structural motifs in loops, and interestingly, it has the capacity to confer internal initiation of translation in tissue culture cells.
| S-EPMC3917987 | biostudies-literature
Project description:Nanotechnology and synthetic biology currently constitute one of the most innovative, interdisciplinary fields of research, poised to radically transform society in the 21st century. This paper concerns the synthetic design of ribonucleic acid molecules, using our recent algorithm, RNAiFold, which can determine all RNA sequences whose minimum free energy secondary structure is a user-specified target structure. Using RNAiFold, we design ten cis-cleaving hammerhead ribozymes, all of which are shown to be functional by a cleavage assay. We additionally use RNAiFold to design a functional cis-cleaving hammerhead as a modular unit of a synthetic larger RNA. Analysis of kinetics on this small set of hammerheads suggests that cleavage rate of computationally designed ribozymes may be correlated with positional entropy, ensemble defect, structural flexibility/rigidity and related measures. Artificial ribozymes have been designed in the past either manually or by SELEX (Systematic Evolution of Ligands by Exponential Enrichment); however, this appears to be the first purely computational design and experimental validation of novel functional ribozymes. RNAiFold is available at http://bioinformatics.bc.edu/clotelab/RNAiFold/.
| S-EPMC4191386 | biostudies-literature
Project description:BackgroundThe ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies.ResultsThe Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization.ConclusionsThe Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".
| S-EPMC4162592 | biostudies-literature