La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching
We introduce La-Ribo, a generative framework for RNA sequence-structure co-design via geometry-latent flow matching.
Key points
- RNA function arises from the coupling of nucleotide sequence and three-dimensional structure, motivating their joint design.
- Coordinating global folding with nucleotide-level detail remains challenging under limited structural supervision.
- La-Ribo retains a sparse phosphate-sugar--base scaffold and encodes nucleotide identity and local conformation in residue-wise latents.
- To expand supervision, we construct a quality-controlled corpus of 168,561 RNA structures, integrating experimental data with predictions from three folding models, including 10,631 MSA-supported structures generated in this work.
Sources (1)
- [1]La-Ribo: RNA Co-Design via Geometry-Latent Flow MatchingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 04:19 PM
We introduce La-Ribo, a generative framework for RNA sequence-structure co-design via geometry-latent flow matching.
RNA function arises from the coupling of nucleotide sequence and three-dimensional structure, motivating their joint design.
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