{
  "abstract": "Automated molecular docking workflows often fail not at the scoring engine but at the interfaces between ligand preparation, protein preparation, binding-site definition, and post-processing. We present RaX-DT, an open-source, Docker Compose–deployable platform that integrates these steps in a single web application and an optional conversational assistant. RaX-DT automates 3D ligand generation, tautomer/protonation-state handling, protein cleaning, binding-site definition via P2Rank, Fpocket, or user-specified coordinates, GNINA-based docking, and interactive result visualization. Because end-to-end automation can introduce silent failures, we validated the assembled workflow on 231 protein–ligand co-crystal structures from DUD-E and LIT-PCBA rather than treating the docking engine in isolation. Of these, 186 structures completed successfully; the top-ranked pose reproduced the crystallographic pose within 2.0 Å for 65.1% of completed structures, and the best of the five top-scoring poses reached 77.4%. Validation also exposed a box-placement defect that would have produced plausible-looking but invalid output, underscoring the value of pipeline-level quality control. RaX-DT is released under the MIT license and is intended to improve accessibility, reproducibility, and transparency in routine docking workflows.",
  "abstract_shown": true,
  "affiliations": [
    "Rare Pediatric Neurological Diseases Research Center",
    "Mashhad University of Medical Sciences",
    "Basic Sciences Research Institute",
    "School of Pharmacy",
    "Pharmaceutical Technology Institute",
    "Neuroscience Research Center",
    "Faculty of Medicine",
    "Faculty of Veterinary Medicine",
    "Shab.C., Islamic Azad University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Amir Hosein Ghavi"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Bita Barazandeh Shirvan"
    },
    {
      "affs": [
        2,
        1
      ],
      "name": "Zohre Ganji"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Zahra Jafari"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Mojgan Nejabat"
    },
    {
      "affs": [
        4,
        1,
        5
      ],
      "name": "Farzin Hadizadeh"
    },
    {
      "affs": [
        0,
        1,
        5
      ],
      "name": "Narges Hashemi"
    },
    {
      "affs": [
        0,
        1,
        6
      ],
      "name": "Javad Akhondian"
    },
    {
      "affs": [
        0,
        1,
        6
      ],
      "name": "Farah Ashrafzadeh"
    },
    {
      "affs": [
        6,
        1
      ],
      "name": "Farnoosh Ebrahimzadeh"
    },
    {
      "affs": [
        6,
        1,
        7,
        8
      ],
      "name": "Mohammad Javad Jafari"
    },
    {
      "affs": [
        0,
        1,
        5
      ],
      "name": "Mehran Beiraghi Toosi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cx1eqyw29g0qd.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15009171/v1",
  "fulltext_url": null,
  "id": "cx1eqyw29g0qd",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009171/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": "W7213945691",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15009171/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-21",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/cx1eqyw29g0qd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:19Z",
      "native_id": "10.26434/chemrxiv.15009171",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009171/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "RaX-DT: An Open-Source Platform for Automated Molecular Docking Workflows and Reproducible Pipeline Validation",
  "title_text": "RaX-DT: An Open-Source Platform for Automated Molecular Docking Workflows and Reproducible Pipeline Validation",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:19Z",
  "url": "https://research.draconitic.com/paper/cx1eqyw29g0qd",
  "venue": "ChemRxiv",
  "versions": []
}