ArticleNature communications2025
Tailoring industrial enzymes for thermostability and activity evolution by the machine learning-based iCASE strategy.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Predicting Enzyme Turnover Numbers and Enabling Rational Enzyme Evolution.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.Comprehensive reviews in food science and food safety · 2026Review
- Magnesium isoglycyrrhizinate alleviates alcohol-associated liver disease through targeting HSD11B1.eLife · 2026Article
- Artificial intelligence and automation in enzyme engineering: evolution, advances, and future perspectives.Bioresources and bioprocessing · 2026Review
- Bridging Algorithms and Biocatalysis: Perspectives on AI-Supported Enzyme Engineering.Molecules (Basel, Switzerland) · 2026Review
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Tryptophanase Mining and Characterization toward the Biological Production of Indole Derivatives.ACS omega · 2026Article
- Improved de novo production of prostaglandin FCommunications biology · 2026Article
- AI-Driven Enzyme Engineering: Emerging Models and Next-Generation Biotechnological Applications.Molecules (Basel, Switzerland) · 2025Review
- Enhancing stability of enzymes for industrial applications: molecular insights and emerging approaches.World journal of microbiology & biotechnology · 2025Review
- Strategic engineering of carbon dots: multi-enzyme mimetics for advanced biomedical intervention in oxidative stress-related diseases.RSC advances · 2025Review
- Engineering PHL7 for improved poly(ethylene terephthalate) depolymerization via rational design and directed evolution.Chem catalysis · 2025Article
- Advanced Pharmaceutical Nanotechnologies Applied for Chinese Herbal Medicines.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Screening, Characterization and Comparison of Endoglucanases/Xylanases from Thermophilic Fungi: AInternational journal of molecular sciences · 2025Article
- Improvement of Catalytic Activity and Thermostability of Alginate Lyase VxAly7B-CM via Rational Computational Design Strategies.Marine drugs · 2025Article
- Tailoring industrial enzymes for thermostability and activity evolution by the machine learning-based iCASE strategy.Nature communications · 2025Article
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9 authors.
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Abstract
The pursuit of obtaining enzymes with high activity and stability remains a grail in enzyme evolution due to the stability-activity trade-off. Here, we develop an isothermal compressibility-assisted dynamic squeezing index perturbation engineering (iCASE) strategy to construct hierarchical modular networks for enzymes of varying complexity. Molecular mechanism analysis elucidates that the peak of adaptive evolution is reached through a structural response mechanism among variants. Furthermore, this dynamic response predictive model using structure-based supervised machine learning is established to predict enzyme function and fitness, demonstrating robust performance across different datasets and reliable prediction for epistasis. The universality of the iCASE strategy is validated by four sorts of enzymes with different structures and catalytic types. This machine learning-based iCASE strategy provides guidance for future research on the fitness evolution of enzymes.
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