{
  "abstract": "Cryptic pockets are druggable sites that are absent in a protein's resting structure and form only upon backbone rearrangement, posing a challenge for detection from static apo structures. Existing methods rely on generating open conformations through sampling or complex prediction, limiting applicability. Here we present a novel detector that reads cryptic pockets directly from a structural world-model latent representation of a single apo structure, without conformational sampling or external pocket finders. Evaluated on CryptoBench and CryptoBank datasets, the method localizes cryptic sites with top-1 accuracy as high as 0.848 and top-5 accuracy exceeding 0.93, and successfully recovers an allosteric site on held-out WRN helicase structures. The detector complements existing approaches and improves with training data scale. These findings suggest that structural world-model latents encode conformational flexibility, enabling effective cryptic pocket identification from apo structures alone, facilitating drug discovery on challenging targets. Benchmarked against the co-folding engine OpenDDE, the detector finds pockets directly rather than by first predicting a bound complex: on 190 targets held out of both training sets it recovers 119 sites OpenDDE misses, against 2 in the other direction, and at top-5 co-folding's recovered sites are a subset of ours. It runs on any structure from the apo coordinates alone, including the mmCIF-only entries all recent depositions carry, and its accuracy keeps climbing as the training corpus grows. The intended use is prospective cryptic-site nomination on the targets that sequence and static structure leave without a starting point.",
  "abstract_shown": true,
  "affiliations": [
    "Eratos Therapeutics"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "R. Shihabi"
    },
    {
      "name": "S. Taraman"
    },
    {
      "name": "B. Vaughan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e6pyy89yyr8th.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.21.752781",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.21.752781v1.full",
  "id": "e6pyy89yyr8th",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.21.752781v1",
  "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",
      "molecular biology"
    ],
    [
      "openalex",
      "1703|Computational Drug Discovery Methods"
    ]
  ],
  "openalex": "W7214034466",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.21.752781v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/e6pyy89yyr8th.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:57Z",
      "native_id": "10.64898/2026.09.21.752781",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.21.752781v2"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "biorxiv:molecular biology",
      "subfield": "molecular-biology"
    }
  ],
  "title": "A World Model of Molecular Organization Detects Cryptic Pockets from Apo Structure",
  "title_text": "A World Model of Molecular Organization Detects Cryptic Pockets from Apo Structure",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:20Z",
  "url": "https://research.draconitic.com/paper/e6pyy89yyr8th",
  "venue": "bioRxiv",
  "versions": []
}