Partial RNA design

Abstract

Motivation: RNA design is a key technique to achieve new functionality in fields like synthetic biology or biotechnology. Computational tools could help to find such RNA sequences but they are often limited in their formulation of the search space.

Results: In this work, we propose partial RNA design, a novel RNA design paradigm that addresses the limitations of current RNA design formulations. Partial RNA design describes the problem of designing RNAs from arbitrary RNA sequences and structure motifs with multiple design goals. By separating the design space from the objectives, our formulation enables the design of RNAs with variable lengths and desired properties, while still allowing precise control over sequence and structure constraints at individual positions. Based on this formulation, we introduce a new algorithm, libLEARNA, capable of efficiently solving different constraint RNA design tasks. A comprehensive analysis of various problems, including a realistic riboswitch design task, reveals the outstanding performance of libLEARNA and its robustness.

Availability and implementation: libLEARNA is open-source and publicly available at: https://github.com/automl/learna_tools.

Figure 1.

Comparison of the first predictions of Meta-LEARNA and libLEARNA on all tasks of the Eterna100 benchmark version 2. The plot shows the average normalized Hamming distance of the first prediction for all tasks of the benchmark. Green bars indicate tasks where libLEARNA achieves lower Hamming distance, and purple bars indicate tasks where the Hamming distance is above that of Meta-LEARNA’s prediction.

Figure 2.

Comparison on randomly masked tasks with balanced brackets.

Figure 3.

Average number of designed riboswitches across different lengths and GC-contents.

Figure 4.

The average energy of RRI complex. A step in the figure corresponds to 500 episodes. The values are averages across five independent runs with standard deviation around the mean displayed as confidence bounds. The dashed red line indicates the energy level of the template sequence in complex with the target RNA.