Flexible RNA design under structure and sequence constraints using formal languages

TL;DR

This paper introduces a formal language-based framework for designing RNA sequences that meet both structural and sequence constraints, enabling efficient and flexible inverse folding solutions with practical biological applications.

Contribution

It develops a novel method using context-free grammars and automata to incorporate complex constraints into RNA design, implemented as a scalable software tool.

Findings

Successfully designed RNA sequences for exon splicing enhancers

Efficiently combined multiple constraints into a single grammar

Implemented a scalable, web-accessible RNA design tool

Abstract

The problem of RNA secondary structure design (also called inverse folding) is the following: given a target secondary structure, one aims to create a sequence that folds into, or is compatible with, a given structure. In several practical applications in biology, additional constraints must be taken into account, such as the presence/absence of regulatory motifs, either at a specific location or anywhere in the sequence. In this study, we investigate the design of RNA sequences from their targeted secondary structure, given these additional sequence constraints. To this purpose, we develop a general framework based on concepts of language theory, namely context-free grammars and finite automata. We efficiently combine a comprehensive set of constraints into a unifying context-free grammar of moderate size. From there, we use generic generic algorithms to perform a (weighted) random generation, or an exhaustive enumeration, of candidate sequences. The resulting method, whose complexity scales linearly with the length of the RNA, was implemented as a standalone program. The resulting software was embedded into a publicly available dedicated web server. The applicability demonstrated of the method on a concrete case study dedicated to Exon Splicing Enhancers, in which our approach was successfully used in the design of \emph{in vitro} experiments.