{
  "abstract": "Prioritizing peptides for closely related G protein-coupled receptors requires comparing target-directed scores with evidence from other structural contexts. We applied the Neurokinin Receptor-Conditioned Peptide Prioritization workflow (NK-RCPP) to 96 generated candidates for neurokinin receptors NK1R, NK2R and NK3R. The retrospective analysis combined receptor-matched on-target REF15 scores with 4,518 paired structural-neighbour comparisons covering 82 candidates. Lower on-target scores than the matched controls were observed for 14/32 NK1R, 23/32 NK2R and 6/32 NK3R candidates. Adding the neighbour-score criterion retained 16 of the 33 evaluable on-target-favoured candidates, reducing that pool by 51.5%. At matched receptor-specific shortlist sizes, half of the candidate identities differed from on-target-only selection. NK2R-04 and NK2R-19 remained selected at the higher neighbour-fraction threshold of 0.75. Fourteen NK2R candidates lacked neighbour summaries, leaving their joint-rule status unresolved. Sequence-frequency and embedding analyses described the candidates within a 1,048-peptide comparison space, and an exploratory 10-peptide NK2R comparison showed differences in standardized scores with uncertain score-potency agreement. These findings show how paired structural-neighbour scoring and threshold choice shape candidate selection within a receptor family. The resulting shortlist provides a defined set for testing whether joint prioritization enriches for active, receptor-preferred peptides.",
  "abstract_shown": true,
  "affiliations": [
    "Huazhong University of Science and Technology"
  ],
  "article_type": "Confirmatory results",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "X. Zhou"
    },
    {
      "name": "H. Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "K. Ning"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/egqv8gpv0s7a6.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.23.761317",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.23.761317v1.full",
  "id": "egqv8gpv0s7a6",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.23.761317v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.23.761317v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-23",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/egqv8gpv0s7a6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:16Z",
      "native_id": "10.64898/2026.10.23.761317",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.23.761317v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "NK-RCPP: a receptor-conditioned computational workflow for prioritizing neurokinin-receptor peptide candidates",
  "title_text": "NK-RCPP: a receptor-conditioned computational workflow for prioritizing neurokinin-receptor peptide candidates",
  "type": "preprint",
  "updated_at": "2026-10-30T12:30:16Z",
  "url": "https://research.draconitic.com/paper/egqv8gpv0s7a6",
  "venue": "bioRxiv",
  "versions": []
}