{
  "abstract": "In standard preparation, AutoDock Vina holds five-and six-membered non-aromatic rings at their input pucker, and our failure analysis of 4 509 runs against searchreachable native poses shows what that costs: with the accurate preset, the search itself fails in only 6.5% of runs, while ring conformations, ranking and the scoring function account for most of the rest. Docking up to four ring conformers per ligand and keeping the best-scoring pose repairs part of that gap for every search we tested, raising top-1 success by 5.5 to 7.4 percentage points for Vina’s Monte Carlo at exhaustiveness 1 and 8 alike and for the two presets we tested it with in the continuous ant colony optimization (ACOR) search we built into Vina; a cost-matched control that docks the input conformer K times shows that most of this gain is ring geometry rather than repeated sampling (+8.9 against +2.9 points with the accurate preset). Because the ensemble multiplies the cost of docking, its price is what limits its use, and this is where the ant colony earns its place: it reaches the pose accuracy of Vina at exhaustiveness 1 with about nine times fewer scoring evaluations, so an ensemble of up to four conformers with the accurate preset costs 8.5 s per ligand on one core and reaches 52.7% top-1 success, against 50.4% for Vina at exhaustiveness 8 (37.9 s) and 46.1% for the same ensemble driven by exhaustiveness 1. Ring ensembles with Vina’s own Monte Carlo at exhaustiveness 8 are the most accurate arm we measured (56.2%), at thirteen times that cost, so the choice between them is one of budget rather than of search.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Suleyman Selim Cinaroglu",
      "orcid": "0000-0001-7120-3540"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/77xj8dx46gqm7.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15009672/v1",
  "fulltext_url": null,
  "id": "77xj8dx46gqm7",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009672/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": "W7214988906",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15009672/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-29",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/77xj8dx46gqm7.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:21Z",
      "native_id": "10.26434/chemrxiv.15009672",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009672/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "Ring-Conformer Ensembles Improve AutoDock Vina Docking; an Ant Colony Makes Them Affordable",
  "title_text": "Ring-Conformer Ensembles Improve AutoDock Vina Docking; an Ant Colony Makes Them Affordable",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:21Z",
  "url": "https://research.draconitic.com/paper/77xj8dx46gqm7",
  "venue": "ChemRxiv",
  "versions": []
}