{
  "abstract": "Non-covalent interactions govern ligand binding specificity and affinity, but existing analysis tools cover a limited set of interaction types, treat metal coordination as a generic contact, and struggle to depict macrocyclic ligands such as heme or cobalamin, leaving comprehensive interaction analysis fragmented across multiple programs. We developed Non-Covalent Interaction Profiler (NCI-Profiler), a free web-based and command-line tool for automated detection and visualization of nine types of protein-ligand non-covalent interactions, including metal coordination and halogen-water-hydrogen (XWH) bridges. NCI-Profiler detects interactions directly from PDB or mmCIF coordinates using literature-derived geometric criteria, without manual structure preparation, and produces interactive 2D diagrams, an in-browser three-dimensional viewer, and downloadable 3D PyMOL sessions, together with structured output files. Its accuracy was validated against 85 literature-annotated complexes and directly compared against PLIP, an established interaction-detection tool, on the same dataset. NCI-Profiler achieved F1-scores of 92-100% for {pi}-{pi} stacking, metal coordination, and water bridges, and 77-83% for the remaining types except hydrophobic contacts (54.8%); it detected literature-confirmed interactions more completely than PLIP in five of nine categories and ran roughly twice as fast. Three case studies further show its expanded coverage can reveal binding-pocket growth vectors, explain structure-activity trends, and distinguish receptor-subtype selectivity. NCI-Profiler is freely available at https://ncip.khu.ac.kr.",
  "abstract_shown": true,
  "affiliations": [
    "Kyung Hee University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "R. Sharma"
    },
    {
      "affs": [
        0
      ],
      "name": "E. Y. Lee"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ad0jxdcgh9971.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.11.758375",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.11.758375v1.full",
  "id": "ad0jxdcgh9971",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.11.758375v1",
  "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",
      "1703|Computational Drug Discovery Methods"
    ]
  ],
  "openalex": "W7222215592",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.11.758375v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-11",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ad0jxdcgh9971.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:52Z",
      "native_id": "10.64898/2026.10.11.758375",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.11.758375v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "NCI-Profiler: automated protein-ligand interaction detection and visualization",
  "title_text": "NCI-Profiler: automated protein-ligand interaction detection and visualization",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:52Z",
  "url": "https://research.draconitic.com/paper/ad0jxdcgh9971",
  "venue": "bioRxiv",
  "versions": []
}