{
  "abstract": "Extremophilic proteins offer immense potential for diverse applications; however, their discovery is hindered by the reliance on predefined templates and domain-specific knowledge. Therefore, new methods are required to mine extremophilic proteins without relying on existing templates, enabling a comprehensive exploration of functional extremophilic proteins across the entire protein universe. Here, we propose a co-evolution-guided protein mining framework, CEM 2.0 (Co-Evolution Mining 2.0), comprising three synergistic components: (1) an extensive and diverse extremophilic proteome database covering six extremophilic features, (2) a multidimensional evaluator for six extremophilic features, leveraging the protein language model ProteinBERT, and (3) an integrated and interactive mining pipeline equipped with advanced tools for computing >20 properties of proteins. This framework was implemented on an interactive web platform (https://cem.sjtu.edu.cn/) equipped with intuitive visualization tools. We conducted wet-lab validation, performed a series of computational validations using published studies, and made recommendations for novel PETases, thereby demonstrating the effectiveness and potential of CEM 2.0 for the template-independent discovery of extremophilic proteins. CEM 2.0 is expected to mine functional extremophilic proteins across the protein universe in terms of evolutionary distance and serve as a valuable tool for protein engineering and synthetic biology.",
  "abstract_shown": true,
  "affiliations": [
    "The State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.",
    "Carbon-Negative Synthetic Biology for Biomaterial Production from CO2 (CNSB), Asia Pacific Graduate Institute of Shanghai Jiao Tong University, Campus for Research Excellence and Technological Enterprise (CREATE), 1 CREATE Way, 138602, Singapore.",
    "The State Key Laboratory of Synergistic Chem-Bio Synthesis, and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zhendong Zhang",
      "orcid": "0009-0004-5123-6539"
    },
    {
      "affs": [
        0
      ],
      "name": "Lina Ma"
    },
    {
      "affs": [
        0
      ],
      "name": "Mingyang Ding"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Ping Xu"
    },
    {
      "affs": [
        2,
        1
      ],
      "name": "Fei Tao"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1enag716wadj0.bib",
  "cited_by": 0,
  "doi": "10.1016/j.engmic.2026.100301",
  "fulltext_url": "https://europepmc.org/articles/PMC13686003",
  "id": "1enag716wadj0",
  "issns": [
    "2667-3703"
  ],
  "landing_url": "https://europepmc.org/article/MED/42910295",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Machine Learning in Bioinformatics"
    ]
  ],
  "openalex": "W7203870088",
  "pdf_url": "https://europepmc.org/articles/PMC13686003?pdf=render",
  "pmcid": "PMC13686003",
  "pmid": "42910295",
  "published": "2026-08-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1enag716wadj0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:14Z",
      "native_id": "MED:42910295",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42910295"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Machine Learning in Bioinformatics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "CEM 2.0: Co-evolution-guided mining of superior extremophilic proteins via a curated proteome database and protein language model.",
  "title_text": "CEM 2.0: Co-evolution-guided mining of superior extremophilic proteins via a curated proteome database and protein language model.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:14Z",
  "url": "https://research.draconitic.com/paper/1enag716wadj0",
  "venue": "Engineering microbiology",
  "versions": []
}