DesiRNA: structure-based design of RNA sequences with a replica exchange Monte Carlo approach

Abstract

Abstract Designing RNA sequences that form a specific structure remains a challenge. Current computational methods often struggle with the complexity of RNA structures, especially when considering pseudoknots or restrictions related to RNA function. We developed DesiRNA, a computational tool for the design of RNA sequences based on the Replica Exchange Monte Carlo approach. It finds sequences that minimize a multiobjective scoring function, fulfill user-defined constraints and minimize the violation of restraints. DesiRNA handles pseudoknots, designs RNA–RNA complexes and sequences with alternative structures, prevents oligomerization of monomers, prevents folding into undesired structures and allows users to specify nucleotide composition preferences. In benchmarking tests, DesiRNA with a default simple scoring function solved all 100 puzzles in the Eterna100 benchmark within 24 h, outperforming all existing RNA design programs. With its ability to address complex RNA design challenges, DesiRNA holds promise for a range of applications in RNA research and therapeutic development.