Polymers· 2026Q1· Review
Advances in Substrate Recognition, Catalytic Mechanisms, and Engineering Applications of Alginate Lyases
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- 2026year
Short summary
Alginate lyases show a critical substrate mismatch: most are characterized on non-acetylated alginate, but their medical target is heavily acetylated bacterial alginate.
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Key points
- Alginate lyases depolymerize alginate via β-elimination, with applications in biorefining and antibiofilm therapy.
- Brown-algal and bacterial alginates differ significantly in O-acetylation, impacting enzyme performance.
- Most enzymological characterization uses non-acetylated alginate, while clinical targets are acetylated bacterial alginates.
- Adapting enzymes to acetylated substrates is the key challenge for medical translation.
AI-generated from the title and abstract; the full text is not read.
Abstract
Alginate lyases depolymerize alginate via β-elimination and serve dual roles in brown-algal biorefining and antibiofilm therapy. Brown-algal and bacterial alginates differ substantially in O-acetylation, yet this key structural distinction and its implications for enzyme performance remain underappreciated. This review systematically integrates the complete causal chain from alginate polymer structure through enzyme recognition, catalytic mechanism, and protein engineering to bidirectional applications. We cover PL family classification, the structural basis of substrate specificity, engineering strategies including two-step activity stability optimization and AI-assisted design, and recent progress in tailored alginate oligosaccharide preparation and cystic fibrosis treatment. Our central analysis identifies a widespread substrate mismatch, as most enzymological characterization relies on non-acetylated sodium alginate, whereas the clinical target is heavily acetylated bacterial alginate. This review establishes acetylated substrate adaptation as the critical gap between fundamental enzymology and medical translation and outlines future directions including multi-objective optimization and AI-driven enzyme design.
The authors' abstract, as published at the source. Polymers, 2026 · DOI ↗
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BiotechnologyBiochemistry, Genetics and Molecular Biology