{
  "abstract": "Recent advances in generative protein design have enabled de novo antibody generation with explicit target and epitope conditioning. However, most existing approaches remain formulated around a single antigen-antibody interface, whereas bispecific antibody design requires modeling multi-component complexes in which multiple target-recognition interfaces must coexist and interact within a shared antibody structure. Here we present OFAntibody, an all-atom generative framework for de novo design of monoclonal and bispecific antibodies. OFAntibody expands CDR-epitope interaction learning with large-scale distilled antigen-antibody complexes, and introduces multi-component structural supervision and arm-aware multi-hotspot routing to learn compatible multi-interface geometries and couple each antibody paratope to its designated epitope. OFAntibody supports epitope-conditioned generation across monoclonal antibodies and diverse bispecific formats, including tandem VHH, diabody and CODV. In nanobody design benchmarks, OFAntibody achieves a Top-5 enrichment rate of 41.5%, representing a 5.39-fold improvement over RFantibody in competitive candidate ranking. In bispecific antibody design tasks, OFAntibody achieves hotspot pass rates of 94-100% across the three evaluated tasks and achieves energy pass rates of 60%, 13% and 8% for diabody, tandem VHH and CODV formats, respectively. OFAntibody further enables the same target combination to be explored across different antibody formats, while joint multi-interface generation reduces geometric incompatibilities arising from independent design and post hoc assembly. Together, these results extend de novo antibody design from binary antigen-antibody complexes to programmable multi-component complexes, providing a foundation for designing single molecules that combine recognition of distinct targets and their associated biological functions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.09548",
  "author_total": 1,
  "authors": [
    {
      "name": "Valhalla Team"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5tm08qg4t0m06.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.09548",
  "fulltext_url": null,
  "id": "5tm08qg4t0m06",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.09548",
  "language": null,
  "licence": "CC-BY-NC-SA-4.0",
  "licence_label": "CC BY-NC-SA 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "q-bio.BM"
    ],
    [
      "openalex",
      "2741|Monoclonal and Polyclonal Antibodies Research"
    ]
  ],
  "openalex": "W7220906035",
  "pdf_url": "https://arxiv.org/pdf/2610.09548",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5tm08qg4t0m06.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:43Z",
      "native_id": "2610.09548",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.09548"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "arxiv:q-bio.BM",
      "subfield": "biophysics"
    }
  ],
  "title": "De novo design of monoclonal and bispecific antibodies with OFAntibody",
  "title_text": "De novo design of monoclonal and bispecific antibodies with OFAntibody",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:43Z",
  "url": "https://research.draconitic.com/paper/5tm08qg4t0m06",
  "venue": "arXiv",
  "versions": []
}