{
  "abstract": "Glucoamylase is essential for industrial starch saccharification, but the limited thermostability and near-neutral pH tolerance of fungal glucoamylases necessitate cooling and acidification of liquefied starch. Here, we developed an artificial intelligence-guided strategy to simultaneously improve the thermostability, pH tolerance, and catalytic activity of glucoamylase from Penicillium oxalicum (PoGA). Two property-specific machine-learning models, CASPE-T and CASPE-A, identified substitutions associated with thermostability and pH tolerance, respectively. Experimental screening identified beneficial substitutions in 11 of 21 CASPE-T and 12 of 22 CASPE-A candidates. Folding-energy-guided recombination integrated the two traits while maintaining structural compatibility. The optimal variant, PoGA T513E/Q305N, exhibited 2.21-fold higher specific activity than the wild type, with half-life extended from 22.3 to 57.9 min at 60 degrees C and from 16.6 to 64.7 min at pH 8.0. Molecular dynamics simulations attributed these improvements to reinforcement of high-occupancy hydrogen-bonding networks, suppression of conformational fluctuations in the linker and carbohydrate-binding module, enhanced long-range dynamic coordination, and preservation of a compact catalytic architecture. At 60 degrees C and pH 6.5 without acidification, PoGA T513E/Q305N produced 219.9 g/L glucose and achieved 89.1% starch conversion, 31.4% higher than the wild type. This work provides an efficient framework for multi-objective enzyme engineering and sustainable starch biorefining.",
  "abstract_shown": true,
  "affiliations": [
    "Nanjing Normal University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "name": "J. QIAO"
    },
    {
      "name": "X. Ma"
    },
    {
      "name": "Y. Song"
    },
    {
      "name": "Q. Deng"
    },
    {
      "name": "X. Ni"
    },
    {
      "name": "G. Liu"
    },
    {
      "name": "S. Meng"
    },
    {
      "name": "F. Shi"
    },
    {
      "name": "L. Deng"
    },
    {
      "name": "H. Cui"
    },
    {
      "affs": [
        0
      ],
      "name": "X. Li"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8a20gkjyds4yb.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.24.753989",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.24.753989v1.full",
  "id": "8a20gkjyds4yb",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.24.753989v1",
  "language": null,
  "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": [
    [
      "biorxiv",
      "synthetic biology"
    ],
    [
      "openalex",
      "1312|Enzyme Catalysis and Immobilization"
    ]
  ],
  "openalex": "W7214161151",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.24.753989v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8a20gkjyds4yb.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:26Z",
      "native_id": "10.64898/2026.09.24.753989",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.24.753989v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:synthetic biology",
      "subfield": "systems-synthetic"
    }
  ],
  "title": "AI-Guided Multi-Objective Engineering of Glucoamylase Enables Acidification-Free Starch Saccharification",
  "title_text": "AI-Guided Multi-Objective Engineering of Glucoamylase Enables Acidification-Free Starch Saccharification",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:26Z",
  "url": "https://research.draconitic.com/paper/8a20gkjyds4yb",
  "venue": "bioRxiv",
  "versions": []
}