{
  "abstract": "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. We introduce La-Ribo, a generative framework for RNA sequence-structure co-design via geometry-latent flow matching. La-Ribo retains a sparse phosphate-sugar--base scaffold and encodes nucleotide identity and local conformation in residue-wise latents. A shared flow network generates both jointly, and an RNA-specific decoder then reconstructs all heavy atoms. 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. La-Ribo improves designability and codesignability over the evaluated baselines across sampling budgets and two refolding models, and the same prior supports scaffold-conditioned inverse folding without additional training.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.12236",
  "author_total": 3,
  "authors": [
    {
      "name": "Runze Ma"
    },
    {
      "name": "Will Hua"
    },
    {
      "name": "Shuangjia Zheng"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/epxhedsvny8m3.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.12236",
  "fulltext_url": null,
  "id": "epxhedsvny8m3",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.12236",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "q-bio.BM"
    ],
    [
      "openalex",
      "1312|RNA and protein synthesis mechanisms"
    ]
  ],
  "openalex": "W7221130275",
  "pdf_url": "https://arxiv.org/pdf/2610.12236",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-08",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/epxhedsvny8m3.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:59Z",
      "native_id": "2610.12236",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.12236"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "arxiv:q-bio.BM",
      "subfield": "biophysics"
    }
  ],
  "title": "La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching",
  "title_text": "La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:59Z",
  "url": "https://research.draconitic.com/paper/epxhedsvny8m3",
  "venue": "arXiv",
  "versions": []
}