Abstract
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.
Highlights
The inverse RNA folding problem for designing sequences that fold into a given RNA secondary structure was introduced in the early 1990’s in Vienna [1]
They all in one way or the other rely at present on thermodynamic parameters corresponding to the nearestneighbor model and structures that are known to be well predicted by energy minimization, for example the secondary structure of the guanine-binding riboswitch aptamer that is illustrated in the second test case example of previous section and in Figure 1, are the best to work with as inputs to these programs in order to achieve reliable results
It is expected that in future, having more experimental structures elucidated, the number of RNA sequences with a well-predicted secondary structure by energy minimization techniques will grow significantly and more biological systems involving RNAs will be designed by the aid of these programs
Summary
The inverse RNA folding problem for designing sequences that fold into a given RNA secondary structure was introduced in the early 1990’s in Vienna [1]. A brute force approach that searches all the possible sequences is not a viable option because the number of sequences grows exponentially as 4n, where n is the length of the sequence, while the number of valid designs can be arbitrarily small. This upper bound can be refined by noting that paired positions have to form valid base pairs under the standard A-U, C-G, G-U base pairing scheme.
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