{
  "abstract": "Chemesthesis constitutes a fundamental dimension of food sensory perception, triggered by transient receptor potential ankyrin 1 (TRPA1) ion channels that mediate responses to pungent and irritating flavor compounds. However, efficient prediction of TRPA1 activation by flavor compounds remains limited by the low throughput of traditional experimental screening. Here, we developed an integrated computational and in vitro pipeline to overcome this limitation. Using an optimized Random Forest (RF) machine learning model, we successfully predicted and screened representative flavor compounds. We empirically validated these predictions using a newly constructed TRPA1 cell line, where calcium flux assays confirmed dose-dependent channel activation by the selected candidates. Furthermore, molecular docking and molecular dynamics simulations elucidated the activation mechanisms at the atomistic level, identifying key interacting residues. This multidisciplinary framework enables efficient targeted screening of sensory receptor ligands and provides deep molecular insights into flavor-driven chemesthetic perception.",
  "abstract_shown": true,
  "affiliations": [
    "Key Laboratory of Tobacco Flavor and Fragrance Basic Research, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China",
    "School of Material Science and Engineering, Zhengzhou University, Zhengzhou, 450001, China"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Xiaoming Wen"
    },
    {
      "affs": [
        0
      ],
      "name": "Qidong Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Shan Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Qingzhao Shi"
    },
    {
      "affs": [
        0
      ],
      "name": "Jingtao Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Wu Fan"
    },
    {
      "affs": [
        1
      ],
      "name": "Shaokang Guan"
    },
    {
      "affs": [
        0
      ],
      "name": "Guobi Chai"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/f5y8vjc4jjxk7.bib",
  "cited_by": 0,
  "doi": "10.1016/j.crfs.2026.101611",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13734784/",
  "id": "f5y8vjc4jjxk7",
  "issns": [
    "2665-9271"
  ],
  "landing_url": "https://doi.org/10.1016/j.crfs.2026.101611",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Research Article"
    ],
    [
      "openalex",
      "2809|Ion Channels and Receptors"
    ]
  ],
  "openalex": "W7223703242",
  "pdf_url": "https://www.sciencedirect.com/science/article/pii/S2665927126003114/pdf",
  "pmcid": "PMC13734784",
  "pmid": "42990872",
  "published": "2026-10-26",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/f5y8vjc4jjxk7.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T12:20:36Z",
      "native_id": "PMC13734784",
      "source": "pmc",
      "url": "https://doi.org/10.1016/j.crfs.2026.101611"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2809|Ion Channels and Receptors",
      "subfield": "neuroscience"
    }
  ],
  "title": "Integrated machine learning and in vitro pipeline for TRPA1-active chemesthetic flavor compounds: From predictive screening to molecular mechanisms",
  "title_text": "Integrated machine learning and in vitro pipeline for TRPA1-active chemesthetic flavor compounds: From predictive screening to molecular mechanisms",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T12:20:36Z",
  "url": "https://research.draconitic.com/paper/f5y8vjc4jjxk7",
  "venue": "Current Research in Food Science",
  "versions": []
}