Abstract
MotivationRealizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility.ResultsWe developed a C ++ library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages.Availability and implementation RNAblueprint, Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
RNA molecules are omnipresent in all domains of life
RNA is a molecule well-suited for designing with predefined functionality. This is mainly due to its close structure to function relationship and the physio-chemically grounded energy models for straightforward in silico calculations at the level of secondary structure
Implementing the complete graph coloring algorithm (Abfalter et al, 2003; Honer zu Siederdissen et al, 2013) and assigning all possible base pairs, RNAblueprint guarantees to uniformly sample the complete solution space. We show that this leads to an extreme value distributed frequency of uniquely found solutions (Fig. 3A). It follows that the solution space, by means of unique solutions generated, can be efficiently explored (Fig. 3B)
Summary
RNA molecules are omnipresent in all domains of life. They execute diverse functions including small molecule sensing, signal transduction and gene regulation. RNA is a molecule well-suited for designing with predefined functionality. This is mainly due to its close structure to function relationship and the physio-chemically grounded energy models for straightforward in silico calculations at the level of secondary structure. Due to the advent of synthetic biology, more researchers are focusing on the design of synthetic RNAs. There has been increasing success in modifying existing systems and incorporating novel functionality in RNAs within a cellular context (Chappell et al, 2015; Espah-Borujeni et al, 2015; Green et al, 2014; Rodrigo et al, 2012)
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