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A Customizable Approach for the Enzymatic Production and Purification of Diterpenoid Natural Products
Published on: October 4, 2019
Engineering class I terpene synthases for skeletal diversity: strategies and applications
Xingming Pan1, Haixin Li1, Liao-Bin Dong1
1State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, China. ldong@cpu.edu.cn.
Engineering terpene synthases (TSs) unlocks diverse natural products. This review details methods like structure-guided design and evolution to create novel terpenoids for medicine and industry.
Area of Science:
- Biochemistry
- Synthetic Biology
- Natural Product Chemistry
Background:
- Terpenoids are nature's largest and most diverse class of natural products.
- Terpene synthases (TSs) are key enzymes responsible for generating structural diversity in terpenoids.
- Applications span medicine, agriculture, and fragrance industries.
Purpose of the Study:
- To review strategies for engineering terpene synthases (TSs) to generate diverse terpene skeletons.
- To highlight key approaches in synthetic biology for terpene production.
- To explore future directions in expanding terpenoid chemical space.
Main Methods:
- Structure-guided design targeting active sites, water networks, and conserved motifs.
- Evolutionary methods using natural variation and phylogenetic insights.
- Mechanism-focused engineering and second-shell modifications.
- Semi-rational and random mutagenesis (e.g., alanine scanning, directed evolution) combined with computational modeling and high-throughput screening.
Main Results:
- Integration of structural biology, computational simulations, and diverse engineering techniques improves outcomes in TS engineering.
- Despite challenges like catalytic complexity and weak sequence-function correlations, progress is steadily being made.
- Advanced screening methods are crucial for identifying successful engineered variants.
Conclusions:
- Engineering TSs is a powerful strategy for accessing novel terpenoid chemical space.
- Future advances in machine learning, mechanistic understanding, and metabolic engineering integration will further enhance biotechnological exploration of terpenoids.
- Continued development of interdisciplinary approaches is vital for unlocking the full potential of TS engineering.
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