RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching

Understand

The growing significance of RNA engineering in diverse biological applications has spurred interest in developing AI methods for structure-based RNA design.

• While diffusion models have excelled in protein design, adapting them for RNA presents new challenges due to RNA's conformational flexibility and the computational cost of fine-tuning large structure prediction models.
• To this end, we propose RNAFlow, a flow matching model for protein-conditioned RNA sequence-structure design.
• Its denoising network integrates an RNA inverse folding model and a pre-trained RosettaFold2NA network for generation of RNA sequences and structures.