{
  "abstract": "Structure-based interface predictors are normally reported as a single pooled ROC AUC over a residue test set. For a protein designer the operative question is different and much harder: given one target chain, will the top-ranked surface patch be a real binding site? We built EpiRank, a partner-agnostic epitope predictor, on HumanPPI 29,246 predicted human dimers, 12,296 target chains, 4.18 M residues using only single-chain geometry and physicochemistry (170 features, no partner, no sequence search, no structural alphabet), and evaluated it as a retrieval problem with homology- and partner-graph-controlled splits, on the 3,529 chains that survive an explicit partner-contamination filter. The model places a real epitope in its top-ranked patch 64 % of the time. That number is far less informative than it looks. Compact patches placed at random hit a real epitope 41 % of the time under the same rule, so the model's lift is 1.57 x, not 64 %; 54 % of all predicted patches land on nothing; and when the same chains are scored by models trained on a 2,000-chain and an 11,669-chain superset, a substantial fraction change answer while the aggregate barely moves. We document four specific ways this task invites overstatement partner-graph percolation across splits, single-linkage homology percolation at the conventional 30 % identity threshold, a count-only hit rule that rewards spatial smoothing rather than signal, and hotspot precision conditioned on success, which ranks a random baseline above the trained model. Each was hit during development and each inverted a conclusion we had already drawn. We argue that interface-prediction papers should report lift over a geometry-matched random baseline, patch precision, and per-target stability alongside AUC, and we release the evaluation harness that computes them.",
  "abstract_shown": true,
  "affiliations": [
    "Astra Biosciences Group"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "B. Lin"
    },
    {
      "name": "D. Lu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7885d3yras62v.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.26.762091",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.26.762091v1.full",
  "id": "7885d3yras62v",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.26.762091v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.26.762091v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7885d3yras62v.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:20:58Z",
      "native_id": "10.64898/2026.10.26.762091",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.26.762091v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "EpiRank: partner-agnostic surface-patch retrieval for epitope prediction of protein binding interfaces",
  "title_text": "EpiRank: partner-agnostic surface-patch retrieval for epitope prediction of protein binding interfaces",
  "type": "preprint",
  "updated_at": "2026-11-02T00:21:21Z",
  "url": "https://research.draconitic.com/paper/7885d3yras62v",
  "venue": "bioRxiv",
  "versions": []
}