{
  "abstract": "Antibiotic resistance is a major threat to public health and calls for chemoinformatic tools that can help the design of antibacterial discovery libraries. We present AB-DB v2.0, a freely available online database of molecular dynamics (MD) trajectories, quantum-mechanical (QM) simulations, force field parameters, and curated physico-chemical descriptors of antimicrobial compounds. AB-DB v2.0 is fully integrated into the Molecular Dynamics Data Bank (MDDB), which provides an interactive web-based environment for visualization, exploration, and on-the-fly analysis of trajectories. QM simulations are included in the ioChem-BD platform, providing a distributed and provenance-tracked repository for computational chemistry results. The database contains more than 470 molecules belonging to 51 antimicrobial classes, including the most relevant families in clinical use, such as $$\\beta$$ β -lactams and quinolones, as well as inhibitors of key bacterial targets and peptide-based agents. Force field parameters and molecular descriptors are available for the major micro-species at physiological pH, ensuring direct reusability in MD, docking, modelling, and machine-learning workflows.\n\nScientific Contribution\n\nBy integrating MD trajectories, QM simulations, force field parameters, and curated physico-chemical descriptors in a single and inter-connected resource, AB-DB v2.0 provides a unique multidimensional framework for antimicrobial data analysis and discovery. This combination enables direct reusability in MD, docking, modelling, and machine-learning workflows.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "name": "Silvia Gervasoni"
    },
    {
      "name": "Genís Bayarri"
    },
    {
      "name": "Andrea Bosin"
    },
    {
      "name": "Attilio V. Vargiu"
    },
    {
      "name": "Modesto Orozco"
    },
    {
      "name": "Adam Hospital"
    },
    {
      "name": "Giuliano Malloci"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5gc6b2kryja1n.bib",
  "cited_by": 0,
  "doi": "10.1186/s13321-026-01314-2",
  "fulltext_url": null,
  "id": "5gc6b2kryja1n",
  "issns": [
    "1758-2946"
  ],
  "landing_url": "https://link.springer.com/article/10.1186/s13321-026-01314-2",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1703|Computational Drug Discovery Methods"
    ]
  ],
  "openalex": "W7223001581",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-20",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/5gc6b2kryja1n.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:48Z",
      "native_id": "10.1186/s13321-026-01314-2",
      "source": "crossref",
      "url": "https://link.springer.com/article/10.1186/s13321-026-01314-2"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "issn:1758-2946",
      "subfield": "theoretical"
    }
  ],
  "title": "AB-DB v2.0: an integrated chemoinformatic resource for antimicrobial compounds",
  "title_text": "AB-DB v2.0: an integrated chemoinformatic resource for antimicrobial compounds",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:48Z",
  "url": "https://research.draconitic.com/paper/5gc6b2kryja1n",
  "venue": "Journal of Cheminformatics",
  "versions": []
}