BeeRNA: tertiary structure-based RNA inverse folding using Artificial Bee Colony

TL;DR

BeeRNA is a novel bio-inspired algorithm using Artificial Bee Colony optimization to design RNA sequences that fold into specific tertiary structures, addressing a complex computational problem in synthetic biology.

Contribution

This work introduces BeeRNA, the first ABC-based method for tertiary RNA inverse folding, combining structural assessment and thermodynamic constraints for improved design accuracy.

Findings

High structural fidelity for RNAs under 100 nucleotides

Efficient CPU runtimes suitable for practical applications

Effective design of microRNAs, aptamers, and ribozymes

Abstract

The Ribonucleic Acid (RNA) inverse folding problem, designing nucleotide sequences that fold into specific tertiary structures, is a fundamental computational biology problem with important applications in synthetic biology and bioengineering. The design of complex three-dimensional RNA architectures remains computationally demanding and mostly unresolved, as most existing approaches focus on secondary structures. In order to address tertiary RNA inverse folding, we present BeeRNA, a bio-inspired method that employs the Artificial Bee Colony (ABC) optimization algorithm. Our approach combines base-pair distance filtering with RMSD-based structural assessment using RhoFold for structure prediction, resulting in a two-stage fitness evaluation strategy. To guarantee biologically plausible sequences with balanced GC content, the algorithm takes thermodynamic constraints and adaptive mutation rates into consideration. In this work, we focus primarily on short and medium-length RNAs ($<$ 100 nucleotides), a biologically significant regime that includes microRNAs (miRNAs), aptamers, and ribozymes, where BeeRNA achieves high structural fidelity with practical CPU runtimes. The lightweight, training-free implementation will be publicly released for reproducibility, offering a promising bio-inspired approach for RNA design in therapeutics and biotechnology.