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LICEDB: light industrial core enzyme database for industrial applications and AI enzyme design

  • Lei Gong
  • , Fufeng Liu
  • , Chuanxi Zhang
  • , Yongfan Ming
  • , Yulan Mou
  • , Zhao Ting Yuan
  • , Haiming Jiang
  • , Bei Gao
  • , Fuping Lu*
  • , Lujia Zhang*
  • *此作品的通讯作者
  • East China Normal University
  • Tianjin University of Science & Technology
  • Shanghai Jiao Tong University
  • School of Automation
  • Inner Mongolia University of Science and Technology
  • East China University of Science and Technology

科研成果: 期刊稿件文章同行评审

摘要

Enzymes, serving as eco-friendly catalysts, are progressively supplanting traditional chemical catalysts in light industry sectors such as feed, papermaking, textiles, detergents, leather, and sugar production. Despite this advancement, the variability in the performance of natural enzymes and the fragmentation and diversity of existing data formats pose significant challenges to researchers. Furthermore, AI-driven enzyme design is limited by the quality and quantity of available data. To address these issues, we introduce the light industrial core enzyme database (LICEDB), the first database dedicated exclusively to managing and standardizing enzymes for light industry applications. LICEDB, with its integrated modules for data retrieval, similarity analysis, and structural analysis, will enhance the efficient industrial application of enzymes and strengthen AI-driven predictive research, thereby advancing data sharing and utilization in the field of enzyme innovation.

源语言英语
文章编号baaf001
期刊Database : the journal of biological databases and curation
2025
DOI
出版状态已出版 - 2025

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 9 - 产业、创新和基础设施
    可持续发展目标 9 产业、创新和基础设施
  2. 可持续发展目标 13 - 气候行动
    可持续发展目标 13 气候行动

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