{
  "abstract": "Epitope-based subunit vaccine design requires chaining together heterogeneous analyses: B-cell antigenicity, topological accessibility, self-tolerance, allergenicity, T-helper/T-cytotoxic immunogenicity, and literature corroboration, historically scattered across separate, often web-only tools. This work presents a computational pipeline that integrates fourteen external tools across eight main phases, runs locally without network calls, and uses content-based self-caching. B-cell antigenicity is assessed via four engines (BepiPred-3.0, EpiDope, DiscoTope-3.0, and ScanNet), whose per-residue scores are fused into a single signal before thresholding. Validation used a panel of seventeen real antigen-antibody complexes from the Protein Data Bank spanning five pathogenic species, with ground truth from structural contact and independent literature verification. Fusing the four engines' scores, completed to a fixed candidate count, outperforms the best individual engine in F1 while reducing predicted residue volume. T-helper and T-cytotoxic immunogenicity are evaluated over each antigen's complete sequence, independently of the B-cell candidates. The final construct retains a B-cell epitope in 13 of 17 structures, and a T-cell block in 13 of 17 antigens, of which 6 match literature-documented epitopes and 2 more show partial correspondence.",
  "abstract_shown": true,
  "affiliations": [
    "Centro Nacional de Biotecnologia (CNB-CSIC)"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "E. L. E. Sierra Vera"
    },
    {
      "name": "B. Pueche Granados"
    },
    {
      "name": "C. E. Gomez"
    },
    {
      "affs": [
        0
      ],
      "name": "C. O. S. Sorzano"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/am0b6w7f0fckt.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.13.758921",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758921v1.full",
  "id": "am0b6w7f0fckt",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758921v1",
  "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",
      "1312|vaccines and immunoinformatics approaches"
    ]
  ],
  "openalex": "W7221772958",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758921v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-13",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/am0b6w7f0fckt.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:48Z",
      "native_id": "10.64898/2026.10.13.758921",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.13.758921v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "BCell-Epitope-Prediction: A local, reproducible pipeline for multi-epitope vaccine design: integration and structural validation against a panel of PDB antigen-antibody complexes",
  "title_text": "BCell-Epitope-Prediction: A local, reproducible pipeline for multi-epitope vaccine design: integration and structural validation against a panel of PDB antigen-antibody complexes",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:48Z",
  "url": "https://research.draconitic.com/paper/am0b6w7f0fckt",
  "venue": "bioRxiv",
  "versions": []
}