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Updated: May 12, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Unlocking Enzyme Discovery: Leveraging Multi-Omics, Machine Learning, and De Novo Design
Hongming Xia1, Chunxiu Zhou1, Baotong Fu1
1Center for Grassland Microbiome, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China.
Abstract:
Enzymes are fundamental protein catalysts essential to life processes and widely applied in industrial and healthcare sectors. However, the broader application of natural enzymes is constrained by their inherent catalytic limitations, and traditional discovery methods such as microbial enrichment are often slow and low-throughput. Driven by advances in multi-omics and artificial intelligence, a range of novel screening strategies has been developed, enabling significant enhancements in both catalytic efficiency and stability of enzymes. This chapter assesses high-throughput approaches, such as metagenomics, metaproteomics, machine learning, and de novo design, comparing their respective advantages and limitations for enzyme discovery. Furthermore, we discuss the application potential of lignocellulose-degrading and plastic-degrading enzymes in biomass conversion and plastic waste recycling.
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