{
  "abstract": "Artificial intelligence (AI)-powered protein structure prediction has transformed how scientists explore macromolecular function. AI-based prediction of macromolecular complexes is increasingly used for evaluating the likelihood of proteins forming complexes with other proteins, nucleic acids, lipids, sugars, or small-molecule ligands. Efficient tools are needed to evaluate these predicted models. We introduce an approach based on combining the confidence metrics of AlphaFold3 to enable clustering of sequence motifs participating in binary interactions and subsequently in 3D interfaces of complexes. Interaction interfaces within confidence limits are finally visualised in 2D using chord diagrams and network graphs. The analysis and visualisation are implemented in a web tool, which links them with interactive graphics and summary tables of predicted interfaces and intermolecular interactions, including confidence scores. Finally, we demonstrate real-life examples of how AlphaBridge is used for providing an efficient way to assess and validate predicted protein complexes and interfaces. The reproducible, objective and automated procedures we present provide a straightforward critical assessment of structure prediction of biomolecular complexes, that should be consulted before conducting more resource-intensive analyses.",
  "abstract_shown": true,
  "affiliations": [
    "Oncode Institute and the Netherlands Cancer Institute Division of Biochemistry, Amsterdam 1066CX, the Netherlands",
    "Oncode Institute and the Netherlands Cancer Institute Division of Biochemistry, Amsterdam 1066CX, the Netherlands. Electronic address: a.perrakis@nki.nl"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Daniel Álvarez Salmoral",
      "orcid": "0009-0009-1407-3909"
    },
    {
      "affs": [
        0
      ],
      "name": "Razvan Borza",
      "orcid": "0000-0003-2759-9511"
    },
    {
      "affs": [
        0
      ],
      "name": "Carmen Maiella",
      "orcid": "0009-0005-5114-5298"
    },
    {
      "affs": [
        0
      ],
      "name": "Bjørn P. Y. Kwee",
      "orcid": "0000-0001-6733-5022"
    },
    {
      "affs": [
        0
      ],
      "name": "Ren Xie"
    },
    {
      "affs": [
        0
      ],
      "name": "Robbie P. Joosten",
      "orcid": "0000-0002-2323-2686"
    },
    {
      "affs": [
        0
      ],
      "name": "Maarten L. Hekkelman",
      "orcid": "0000-0002-9081-4707"
    },
    {
      "affs": [
        1
      ],
      "name": "Anastassis Perrakis A",
      "orcid": "0000-0002-1151-6227"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3vf1h1n2kcm93.bib",
  "cited_by": 50,
  "doi": "10.1016/j.str.2026.08.011",
  "fulltext_url": null,
  "id": "3vf1h1n2kcm93",
  "issns": [
    "0969-2126",
    "1878-4186"
  ],
  "landing_url": "https://doi.org/10.1016/j.str.2026.08.011",
  "language": "en",
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Protein Structure and Dynamics"
    ]
  ],
  "openalex": "W7213424650",
  "pdf_url": null,
  "pmcid": null,
  "pmid": "42748924",
  "published": "2026-09-01",
  "publisher": "Elsevier BV",
  "ris": "https://research.draconitic.com/paper/3vf1h1n2kcm93.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:26:46Z",
      "native_id": "W7213424650",
      "source": "openalex",
      "url": "https://doi.org/10.1016/j.str.2026.08.011"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Protein Structure and Dynamics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "AlphaBridge: Tools for the analysis of predicted biomolecular complexes",
  "title_text": "AlphaBridge: Tools for the analysis of predicted biomolecular complexes",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T13:21:05Z",
  "url": "https://research.draconitic.com/paper/3vf1h1n2kcm93",
  "venue": "Structure",
  "versions": []
}