MODENA: a multi-objective RNA inverse folding

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/

Multi-Objective Genetic Algorithm for Pseudoknotted RNA Sequence Design

RNA inverse folding is a computational technology for designing RNA sequences which fold into a user-specified secondary structure. Although pseudoknots are functionally important motifs in RNA structures, less reports concerning the inverse folding of pseudoknotted RNAs have been done compared to those for pseudoknot-free RNA design. In this paper, we present a new version of our multi-objective genetic algorithm (MOGA), MODENA, which we have previously proposed for pseudoknot-free RNA inverse folding. In the new version of MODENA, (i) a new crossover operator is implemented and (ii) pseudoknot prediction methods, IPknot and HotKnots, are used to evaluate the designed RNA sequences, allowing us to perform the inverse folding of pseudoknotted RNAs. The new version of MODENA with the new crossover operator was benchmarked with a dataset composed of natural pseudoknotted RNA secondary structures, and we found that MODENA can successfully design more pseudoknotted RNAs compared to the other pseudoknot design algorithm. In addition, a sequence constraint function newly implemented in the new version of MODENA was tested by designing RNA sequences which fold into the pseudoknotted structure of a hepatitis delta virus ribozyme; as a result, we successfully designed eight RNA sequences. The new version of MODENA is downloadable from http://rna.eit.hirosaki-u.ac.jp/modena/

INFO-RNA—a server for fast inverse RNA folding satisfying sequence constraints

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

A global sampling approach to designing and reengineering RNA secondary structures

The development of algorithms for designing artificial RNA sequences that fold into specific secondary structures has many potential biomedical and synthetic biology applications. To date, this problem remains computationally difficult, and current strategies to address it resort to heuristics and stochastic search techniques. The most popular methods consist of two steps: First a random seed sequence is generated; next, this seed is progressively modified (i.e. mutated) to adopt the desired folding properties. Although computationally inexpensive, this approach raises several questions such as (i) the influence of the seed; and (ii) the efficiency of single-path directed searches that may be affected by energy barriers in the mutational landscape. In this article, we present RNA-ensign, a novel paradigm for RNA design. Instead of taking a progressive adaptive walk driven by local search criteria, we use an efficient global sampling algorithm to examine large regions of the mutational landscape under structural and thermodynamical constraints until a solution is found. When considering the influence of the seeds and the target secondary structures, our results show that, compared to single-path directed searches, our approach is more robust, succeeds more often and generates more thermodynamically stable sequences. An ensemble approach to RNA design is thus well worth pursuing as a complement to existing approaches. RNA-ensign is available at http://csb.cs.mcgill.ca/RNAensign.National Science Foundation (U.S.). Graduate Research Fellowship ProgramNatural Sciences and Engineering Research Council of Canada (NSERC) (RGPIN ) (386596-10)Fonds québécois de la recherche sur la nature et les technologies (PR-146375)National Institutes of Health (U.S.) (Grant GM081871)Natural Sciences and Engineering Research Council of Canada (NSERC)National Institutes of Health (U.S.

Inverse folding of RNA pseudoknot structures

Background: RNA exhibits a variety of structural configurations. Here we consider a structure to be tantamount to the noncrossing Watson-Crick and \pairGU-base pairings (secondary structure) and additional cross-serial base pairs. These interactions are called pseudoknots and are observed across the whole spectrum of RNA functionalities. In the context of studying natural RNA structures, searching for new ribozymes and designing artificial RNA, it is of interest to find RNA sequences folding into a specific structure and to analyze their induced neutral networks. Since the established inverse folding algorithms, {\tt RNAinverse}, {\tt RNA-SSD} as well as {\tt INFO-RNA} are limited to RNA secondary structures, we present in this paper the inverse folding algorithm {\tt Inv} which can deal with 3-noncrossing, canonical pseudoknot structures. Results: In this paper we present the inverse folding algorithm {\tt Inv}. We give a detailed analysis of {\tt Inv}, including pseudocodes. We show that {\tt Inv} allows to design in particular 3-noncrossing nonplanar RNA pseudoknot 3-noncrossing RNA structures-a class which is difficult to construct via dynamic programming routines. {\tt Inv} is freely available at \url{http://www.combinatorics.cn/cbpc/inv.html}. Conclusions: The algorithm {\tt Inv} extends inverse folding capabilities to RNA pseudoknot structures. In comparison with {\tt RNAinverse} it uses new ideas, for instance by considering sets of competing structures. As a result, {\tt Inv} is not only able to find novel sequences even for RNA secondary structures, it does so in the context of competing structures that potentially exhibit cross-serial interactions.Comment: 20 pages, 26 figure

Functional nucleic acids as substrate for information processing

Information processing applications driven by self-assembly and conformation dynamics of nucleic acids are possible. These underlying paradigms (self-assembly and conformation dynamics) are essential for natural information processors as illustrated by proteins. A key advantage in utilising nucleic acids as information processors is the availability of computational tools to support the design process. This provides us with a platform to develop an integrated environment in which an orchestration of molecular building blocks can be realised. Strict arbitrary control over the design of these computational nucleic acids is not feasible. The microphysical behaviour of these molecular materials must be taken into consideration during the design phase. This thesis investigated, to what extent the construction of molecular building blocks for a particular purpose is possible with the support of a software environment. In this work we developed a computational protocol that functions on a multi-molecular level, which enable us to directly incorporate the dynamic characteristics of nucleic acids molecules. To allow the implementation of this computational protocol, we developed a designer that able to solve the nucleic acids inverse prediction problem, not only in the multi-stable states level, but also include the interactions among molecules that occur in each meta-stable state. The realisation of our computational protocol are evaluated by generating computational nucleic acids units that resembles synthetic RNA devices that have been successfully implemented in the laboratory. Furthermore, we demonstrated the feasibility of the protocol to design various types of computational units. The accuracy and diversity of the generated candidates are significantly better than the best candidates produced by conventional designers. With the computational protocol, the design of nucleic acid information processor using a network of interconnecting nucleic acids is now feasible