@@ -160,9 +160,9 @@ Sebastian Will\orcidID{0000-0002-2376-9205}
\section{Introduction}
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Designing molecules with novel functionality or very specific desirable properties for applications in biological fundamental research, biotechnology, and medicine, is a highly complex task that typically requires interdisciplinary efforts, combining biochemical experimentation and computational design. Compared to proteins, designing RNAs can be particularly attractive for the construction of new biotechnological devices. On the one hand, functional RNA molecules save the detour of translation into proteins, and can therefore act more efficiently, e.g. as fast on/off-switches of gene activity. On the other hand, the design process itself can build on the well-understood combinatorics of RNA secondary structure and available computational models and algorithms.
Designing molecules with novel functionality or very specific desirable properties for applications in biological fundamental research, biotechnology, and medicine, is a highly complex task that typically requires interdisciplinary efforts, combining biochemical experimentation and computational design~\cite{Hammer2019}. Compared to proteins, designing RNAs can be particularly attractive for the construction of new biotechnological devices. Functional RNA molecules save the detour of translation into proteins, and can therefore act more efficiently, e.g. as fast on/off-switches of gene activity. On the other hand, the design process itself can build on the well-understood combinatorics of RNA secondary structure and available computational models and algorithms.
Still, the supporting RNA design computationally is highly demanding. First of all, RNA design is an optimization problem with often complex objectives with respect to multiple (secondary) structures, e.g. when the designed RNAs should switch between alternative structural states or fold via specific intermediary structures. Moreover, RNA design is computationally complex even in simple problem variants. For example, one cannot efficiently design an RNA that preferentially folds into a single given target structure in the nearest-neighbor energy model, since this problem is NP-hard.
Still, the supporting RNA design computationally is highly demanding. First of all, RNA design is an optimization problem with often complex objectives with respect to multiple (secondary) structures, e.g. when the designed RNAs should switch between alternative structural states or fold via specific intermediary structures. Moreover, RNA design is computationally complex even in simple problem variants. For example, one cannot efficiently design an RNA that preferentially folds into a single given target structure in the simple base pair energy model, since this problem is NP-hard~\cite{bonnet2020designing}.
Here we present the framework \Infrared, which addresses the multiple demands of computational RNA design in several ways:
