{
  "id": 5125,
  "url": "https://arxiv.org/abs/2605.02937v1",
  "title": "Proteo-R1: Reasoning Foundation Models for De Novo Protein Design",
  "summary": "Deep learning in \\emph{de novo} protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synthesize molecular geometries without explicitly reasoning about which residues or interactions are functionally essential. As a result, design decisions are entangled with continuous sampling dynamics, limiting interpretability, controllability, and systematic reuse of biochemical knowledge. We introduce \\textbf{Proteo-R1}, a reasoning-guid",
  "authors": "Fang Wu, Weihao Xuan, Heli Qi, Hanqun Cao, Heng-Jui Chang, Zeqi Zhou et al.",
  "category": "research",
  "topics": "safety-alignment,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-01T06:52:27.000Z",
  "fetched_at": "2026-07-14T16:31:31.212Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5125",
  "original_url": "https://arxiv.org/abs/2605.02937v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}