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 |
| 卷 | 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:
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可持续发展目标 9 产业、创新和基础设施
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可持续发展目标 13 气候行动
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