{
  "abstract": "Large language model (LLM) agents have shown promise in driving scientific discovery, but their effectiveness in complex, real-world biological problems remains underexplored. We ask whether a general-purpose LLM agent can drive semi-autonomous development of a model for a genuinely hard biological problem, RNA 3D structure prediction. We designed a development loop where, under a fixed budget and with human supervision, the agent iteratively proposed, implemented, trained, and evaluated model changes. Over 297 iterations, the model evolved from a randomly-initialised baseline to QuickFold, an 8.9M-parameter folding trunk that matches the strongest open-source baselines (RhoFold+, NuFold) on lDDT and TM-score within noise on a held-out test set at a fraction of their inference cost. We frame this less as a new predictor than as a case study in feedback-driven, agent-led model development.",
  "abstract_shown": true,
  "affiliations": [
    "Sanofi"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "M. Majewski"
    },
    {
      "name": "L. Malo"
    },
    {
      "name": "A. Montero-Blay"
    },
    {
      "name": "M. Marengo"
    },
    {
      "name": "P. Gkeka"
    },
    {
      "name": "H. Minoux"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bw030rxxtwbs8.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.08.749228",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.08.749228v1.full",
  "id": "bw030rxxtwbs8",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.08.749228v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1312|RNA and protein synthesis mechanisms"
    ]
  ],
  "openalex": "W7212024955",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.08.749228v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-08",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bw030rxxtwbs8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:28Z",
      "native_id": "10.64898/2026.09.08.749228",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.08.749228v2"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Agent-driven Model Development for RNA 3D Structure Prediction",
  "title_text": "Agent-driven Model Development for RNA 3D Structure Prediction",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:55Z",
  "url": "https://research.draconitic.com/paper/bw030rxxtwbs8",
  "venue": "bioRxiv",
  "versions": []
}