{
  "abstract": "Identifying new chemical entities for small molecule drug discovery requires the continued exploration of its vast chemical space, which has been speculated to contain 10⁶⁰ or more molecules. Here we used generative artificial intelligence to sample a GDB-20 database estimated to contain 32 trillion organic molecules corresponding to 26.9 million molecular graphs up to 20 nodes selected for their limited topological complexity. We show that GDB-20 populates a distinct chemical space of sp³-rich, 3D-shaped and natural product-like molecules with favorable synthetic accessibility score. The relevance for drug discovery of our 12 billion sample, named GDB-20s and corresponding in size to approximately 0.04% of the estimated full database, is suggested by high compliance with drug-likeness and toxicity filters, and the coverage of thousands of scaffolds occurring in bioactive molecules recorded in the ChEMBL database. The generative models used to produce GDB-20s, together with the 12-billion-molecule collection are available for download at https://gdb.unibe.ch.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern Bern 3012 Switzerland jean-louis.reymond@unibe.ch."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ye Buehler",
      "orcid": "0000-0002-8139-830X"
    },
    {
      "affs": [
        0
      ],
      "name": "Sacha Javor"
    },
    {
      "affs": [
        0
      ],
      "name": "Jean-Louis Reymond",
      "orcid": "0000-0003-2724-2942"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/09j7zvdz5qpw1.bib",
  "cited_by": 0,
  "doi": "10.1039/d6dd00213g",
  "fulltext_url": "https://europepmc.org/articles/PMC13711157",
  "id": "09j7zvdz5qpw1",
  "issns": [
    "2635-098X"
  ],
  "landing_url": "https://europepmc.org/article/MED/42948043",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Chemistry"
    ],
    [
      "openalex",
      "1703|Computational Drug Discovery Methods"
    ]
  ],
  "openalex": "W7222746565",
  "pdf_url": "https://pubs.rsc.org/dd/article-pdf/doi/10.1039/D6DD00213G/14907968/d6dd00213g.pdf",
  "pmcid": "PMC13711157",
  "pmid": "42948043",
  "published": "2026-10-16",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/09j7zvdz5qpw1.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:34Z",
      "native_id": "MED:42948043",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42948043"
    },
    {
      "first_seen": "2026-10-31T12:21:59Z",
      "native_id": "PMC13711157",
      "source": "pmc",
      "url": "https://doi.org/10.1039/d6dd00213g"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "heading:Chemistry",
      "subfield": "general"
    }
  ],
  "title": "Sampling a trillion-sized GDB-20 database of drug-like molecules by generative artificial intelligence.",
  "title_text": "Sampling a trillion-sized GDB-20 database of drug-like molecules by generative artificial intelligence.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-31T12:21:59Z",
  "url": "https://research.draconitic.com/paper/09j7zvdz5qpw1",
  "venue": "Digital discovery",
  "versions": []
}