{
  "abstract": "De novo protein-binder design with deep-learning pipelines such as BindCraft2 has been reported to deliver experimental success rates of 10-100% against well-structured targets. Here we report the opposite tail: two BindCraft2 (v1.0.3) cyclic-peptide campaigns targeting the shallow K81 lactylation epitope of human lactate dehydrogenase A (LDHA) produced zero accepted designs from 627 trajectories. Retrospective analysis of the campaign artifacts shows that 97% of trajectories were rejected at the first (\"screen\") stage by a single confidence gate (binder pLDDT < 0.60), not because the interface failed to form: the interface metric i_pTM reached 0.69 and the target was confidently folded (pTM = 0.90). Critically, the mid-project decision to disable the \"lysine trick\" (forced_targeting) was backwards -- that feature moved 17 trajectories past the screen versus 1 without it, and raised interface confidence. We document two preset/metric mismatches that set a macrocycle campaign up to fail regardless of budget: a screen-stage pLDDT gate calibrated for globular binders, and a binder_contacts loss that is degenerate for short peptides. We describe the exact artifacts BindCraft2 writes and distill them into a reusable post-mortem protocol, and we include a complete how-to-use-BindCraft2 guide so the failure analysis also serves as a tutorial.",
  "abstract_shown": true,
  "affiliations": [
    "Shenzhen UniBindMD Computational Biotechnology Co., Ltd."
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "W. Fu"
    },
    {
      "name": "J. Chen"
    },
    {
      "name": "X. Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2m5vzn43krdzp.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.13.758722",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758722v1.full",
  "id": "2m5vzn43krdzp",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758722v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1312|Protein Structure and Dynamics"
    ]
  ],
  "openalex": "W7221937254",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758722v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-13",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2m5vzn43krdzp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:53Z",
      "native_id": "10.64898/2026.10.13.758722",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758722v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Why 627 BindCraft2 trajectories produced zero binders",
  "title_text": "Why 627 BindCraft2 trajectories produced zero binders",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:53Z",
  "url": "https://research.draconitic.com/paper/2m5vzn43krdzp",
  "venue": "bioRxiv",
  "versions": []
}