Assaf Avihoo

RNAexinv: An extended inverse RNA folding from shape and physical attributes to sequences

BackgroundRNAexinv is an interactive java application that performs RNA sequence design, constrained to yield a specific RNA shape and physical attributes. It is an extended inverse RNA folding program with the rationale behind that the generated sequences should not only fold into a desired structure, but they should also exhibit favorable attributes such as thermodynamic stability and mutational robustness. RNAexinv considers not only the secondary structure in order to design sequences, but also the mutational robustness and the minimum free energy. The sequences that are generated may not fully conform with the given RNA secondary structure, but they will strictly conform with the RNA shape of the given secondary structure and thereby take into consideration the recommended values of thermodynamic stability and mutational robustness that are provided.ResultsThe output consists of designed sequences that are generated by the proposed method. Selecting a sequence displays the secondary structure drawings of the target and the predicted fold of the sequence, including some basic information about the desired and achieved thermodynamic stability and mutational robustness. RNAexinv can be used successfully without prior experience, simply specifying an initial RNA secondary structure in dot-bracket notation and numerical values for the desired neutrality and minimum free energy. The package runs under LINUX operating system. Secondary structure predictions are performed using the Vienna RNA package.ConclusionsRNAexinv is a user friendly tool that can be used for RNA sequence design. It is especially useful in cases where a functional stem-loop structure of a natural sequence should be strictly kept in the designed sequences but a distant motif in the rest of the structure may contain one more or less nucleotide at the expense of another, as long as the global shape is preserved. This allows the insertion of physical observables as constraints. RNAexinv is available at http://www.cs.bgu.ac.il/~RNAexinv.

Reconstruction of natural RNA sequences from RNA shape, thermodynamic stability, mutational robustness, and linguistic complexity by evolutionary computation.

Abstract The process of designing novel RNA sequences by inverse RNA folding, available in tools such as RNAinverse and InfoRNA, can be thought of as a reconstruction of RNAs from secondary structure. In this reconstruction problem, no physical measures are considered as additional constraints that are independent of structure, aside of the goal to reach the same secondary structure as the input using energy minimization methods. An extension of the reconstruction problem can be formulated since in many cases of natural RNAs, it is desired to analyze the sequence and structure of RNA molecules using various physical quantifiable measures. In prior works that used secondary structure predictions, it has been shown that natural RNAs differ significantly from random RNAs in some of these measures. Thus, we relax the problem of reconstructing RNAs from secondary structure into reconstructing RNAs from shapes, and in turn incorporate physical quantities as constraints. This allows for the design of novel RNA sequences by inverse folding while considering various physical quantities of interest such as thermodynamic stability, mutational robustness, and linguistic complexity. At the expense of altering the number of nucleotides in stems and loops, for example, physical measures can be taken into account. We use evolutionary computation for the new reconstruction problem and illustrate the procedure on various natural RNAs.

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

SUMMARY In RNA design problems, it is plausible to assume that the user would be interested in preserving a particular RNA secondary structure motif, or fragment, for biological reasons. The preservation could be in structure or sequence, or both. Thus, the inverse RNA folding problem could benefit from considering fragment constraints. We have developed a new interactive Java application called RNA fragment-based inverse that allows users to insert an RNA secondary structure in dot-bracket notation. It then performs sequence design that conforms to the shape of the input secondary structure, the specified thermodynamic stability, the specified mutational robustness and the user-selected fragment after shape decomposition. In this shape-based design approach, specific RNA structural motifs with known biological functions are strictly enforced, while others can possess more flexibility in their structure in favor of preserving physical attributes and additional constraints. AVAILABILITY 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.

RNAthermsw: Direct Temperature Simulations for Predicting the Location of RNA Thermometers

The mechanism of RNA thermometers is a subject of growing interest. Also known as RNA thermosensors, these temperature-sensitive segments of the mRNA regulate gene expression by changing their secondary structure in response to temperature fluctuations. The detection of RNA thermometers in various genes of interest is valuable as it could lead to the discovery of new thermometers participating in fundamental processes such as preferential translation during heat-shock. RNAthermsw is a user-friendly webserver for predicting the location of RNA thermometers using direct temperature simulations. It operates by analyzing dotted figures generated as a result of a moving window that performs successive energy minimization folding predictions. Inputs include the RNA sequence, window size, and desired temperature change. RNAthermsw can be freely accessed at http://www.cs.bgu.ac.il/~rnathemsw/RNAthemsw/ (with the slash sign at the end). The website contains a help page with explanations regarding the exact usage.

Shape similarity measures for the design of small RNA switches

Abstract Conformational switching in the secondary structure of RNAs has recently attracted considerable attention, fostered by the discovery of ‘riboswitches’ in living organisms. These are genetic control elements that were found in bacteria and offer a unique regulation mechanism based on switching between two highly stable states, separated by an energy barrier between them. In riboswitches, the energy barrier is crossed by direct metabolite binding, which facilitates regulation by allosteric means. However, other event triggers can cause switching to occur, such as single-point mutations and slight variations in temperature. Examples of switches with these event triggers have already been reported experimentally in the past. Here, the goal is to computationally design small RNA switches that rely on these triggers. Towards this end, our computer simulations utilize a variety of different similarity measures to assess the distances between an initial state and triggered states, based on the topology of the secondary structure itself. We describe these combined similarity measures that rely on both coarse-grained and fine-grained graph representations of the RNA secondary structure. As a result of our simulations, we provide some candidate sequences of approximately 30–50 nt, along with the exact triggers that drive the switching. The event triggers under consideration can be modelled by Zukers mfold or the Vienna package. The proposed methodology that rely on shape measures can further be used to computationally generate more candidates by simulating various event triggers and calculating their effect on the shape.

Fine-grain matrix graph representation for predicting mutations leading to conformational rearrangements in small RNAs

Previously, it was shown that predicting selective mutations leading to topological transitions in the secondary structure of RNAs can be achieved by a coarse-grain Laplacian matrix tree graph representation using its second eigenvalue. When applying the coarse-grain tree graph representation, introduced by Shapiro and coworkers in the 80s, it is possible to predict mutations leading to conformational rearrangements in RNAs of around 50 nt and higher. However, for small RNAs, such representations at the level of stems, bulges, and loops become ineffective. Recently, there is an interest in investigating secondary structure rearrangements in small RNAs, following their structural probing by comparative imino proton NMR spectroscopy. For computational predictions of mutations leading to the structure rearrangements of small RNAs, it is necessary to use a fine-grain graph representation as introduced by Waterman in the 70s at the level of nucleotides. Each nucleotide becomes a node in the graph and its equivalent Laplacian matrix is of the size N /spl times/ N for a sequence of N nucleotides. Conformational rearrangements caused by mutations can be studied using measures to assess the differences between Laplacian matrices of fine-grain graph representations. The second eigenvalue of the Laplacian matrix can be used to filter mutations that lead to a structure similar to the wildtype but additional measures are needed. Image analysis techniques, by moving a sliding window over Laplacian matrices, can facilitate in differentiating between local rearrangements and global rearrangements.