{
  "abstract": "Structure-based virtual screening serves as a primary approach for ligand prioritization from large molecular libraries, but accurately predicting the activity of chemical entities on novel drug targets remains a formidable challenge. Here, we present an interactome-based graph transformer network for rapid bioactivity prediction and de novo ligand design. Integrating three-dimensional pocket geometry with two-dimensional ligand graphs yields a joint representation for direct affinity prediction, which generalizes well across sparse datasets. To validate practical utility, we performed a zero-shot generative ligand design to identify scaffold hops from the complex natural product ibogaine, a noncompetitive inhibitor of the serotonin transporter. The top-ranked design and its rational analogs were synthesized and exhibited equipotent isofunctional in vitro activity alongside favorable pharmacokinetic properties directly upon initial generation. This workflow establishes a blueprint for molecular engineering that seamlessly bridges the automated design of lead-like, synthetically accessible small molecules with efficient bioactivity prediction.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Biosystems Science and Engineering, Molecular Design Laboratory, ETH Zurich, Klingelbergstrasse 48, Basel, Switzerland, 4056",
    "Roche Pharma Research and Early Development (pRED, Hoffmann-La Roche Ltd., Grenzacherstrasse 124, Basel, Switzerland, 4070"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Irene Pachon-Angona"
    },
    {
      "affs": [
        0
      ],
      "name": "Carl C. G. Schiebroek"
    },
    {
      "affs": [
        0
      ],
      "name": "Manuel G. Schriefer Treiber"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Mattis Hilleke"
    },
    {
      "affs": [
        0
      ],
      "name": "Michael Iff"
    },
    {
      "affs": [
        1
      ],
      "name": "Achi Haider"
    },
    {
      "affs": [
        0
      ],
      "name": "Petra Schneider"
    },
    {
      "affs": [
        1
      ],
      "name": "Uwe Grether"
    },
    {
      "affs": [
        0
      ],
      "name": "Stephan Allenspach"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Kenneth Atz"
    },
    {
      "affs": [
        0
      ],
      "name": "Gisbert Schneider"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cwhr55zxqdf3c.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15008337/v1",
  "fulltext_url": null,
  "id": "cwhr55zxqdf3c",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008337/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1703|Computational Drug Discovery Methods"
    ]
  ],
  "openalex": "W7208705350",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-04",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/cwhr55zxqdf3c.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:17Z",
      "native_id": "10.26434/chemrxiv.15008337",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008337/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "Deep drug design for molecular scaffold hopping",
  "title_text": "Deep drug design for molecular scaffold hopping",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:17Z",
  "url": "https://research.draconitic.com/paper/cwhr55zxqdf3c",
  "venue": "ChemRxiv",
  "versions": []
}