Engineering a Seven Enzyme Biotransformation using Mathematical Modelling and Characterized Enzyme Parts

Area of Science:

• Biocatalysis and metabolic engineering
• Enzyme engineering and process development

Background:

• Multi-step enzyme reactions offer significant cost and productivity advantages.
• Process models are crucial for understanding and optimizing complex enzymatic reactions.
• Few process models exist for multi-step in vitro enzyme reactions.

Purpose of the Study:

• To construct and validate a process model for a complex, multi-step enzymatic biotransformation.
• To demonstrate the utility of process models in identifying and resolving bottlenecks.
• To optimize the entire reaction pathway using computational methods.

Main Methods:

• Construction of a process model using a toolbox of characterized enzyme parts.
• Incorporation of enzymes for cofactor regeneration to ensure reaction economy.
• Application of good modeling practices to assess approximations and experimental errors.
• Utilizing a genetic algorithm for the optimization of the multi-step reaction.

Main Results:

• Successfully constructed a process model for a seven-enzyme, three-step biotransformation.
• Process model validation was instrumental in identifying and resolving process bottlenecks.
• Demonstrated reliable modeling and optimization of complex enzymatic reactions with cofactor recycling.
• Achieved optimization of the entire reaction pathway.

Conclusions:

• Complex multi-step enzymatic reactions, even those with cofactor recycling and multiple enzymes, can be reliably modeled and optimized.
• Process modeling is a critical tool for advancing biocatalysis and improving efficiency.
• This work provides a framework for the development of process models for other complex enzymatic systems.