{
  "id": 8076675,
  "title": "Integrating complementary biological information for multi-objective enzyme engineering",
  "url": "https://urgent.news/2026/09/17/integrating-complementary-biological-information-for-multi-objective",
  "topic": "science",
  "section": "Science",
  "published": "2026-09-17T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.15.751856v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Enzyme catalysts are increasingly used for sustainable pharmaceutical manufacturing, but engineering industrial biocatalysts remains challenging as multiple catalytic and developability properties must be optimized simultaneously from limited experimental data. Here, we develop a machine learning-guided multi-objective design framework that integrates sparse functional measurements with…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}