Structure-alignment-driven cross-graph modeling for functional RNA design

RNAs are critical for biological processes, and their functions are closely tied to their three-dimensional structures. The design of RNA sequences that fold into target three-dimensional structures is a complex challenge due to the dynamic and unstable nature of RNA structures. Here we present an RNA design approach, AlignIF, that leverages multiple structure alignment with cross-graph modeling and carefully hand-designed features to capture evolutionarily conserved structural patterns at the structural level, facilitating RNA sequence design. AlignIF outperforms existing state-of-the-art methods in test sets. Notably, it enables the design of entire RNA families rather than being restricted to recapitulating native sequences. Furthermore, AlignIF successfully designs functional RNA fluorescent aptamers and self-cleaving ribozymes that exhibit measurable activity without requiring any postdesign filtering. For Mango-I, two of ten designed aptamers showed enhanced fluorescence, and two others exhibited improved binding affinity compared with the wild type. For the more challenging iMango-III, all designs were fluorescent, including one with a sequence identity of ~30% relative to the wild type. The results highlight the potential of AlignIF for functional RNA engineering.

Wang, S., Wang, J., Liu, X. et al. Structure-alignment-driven cross-graph modeling for functional RNA design.
Nat Comput Sci (2026). https://doi.org/10.1038/s43588-026-01029-2

https://doi.org/10.1038/s43588-026-01029-2