Chemoinformatic-Guided Engineering of Polyketide Synthases.

Area of Science:

• Biotechnology
• Synthetic Biology
• Chemical Engineering

Background:

• Polyketide synthases (PKS) are crucial for producing diverse molecules.
• Engineering PKS modules, particularly for saturated β-carbon production via reductive loop (RL) exchange, presents a significant challenge.
• Chemoinformatics, typically used in drug discovery, has not been widely applied to PKS engineering.

Purpose of the Study:

• To establish chemoinformatics as a viable strategy for PKS reductive loop (RL) exchanges.
• To demonstrate the utility of RL exchange for generating novel chemical products.
• To correlate chemical structure similarity with production yields in engineered PKS systems.

Main Methods:

• Introduced diverse donor RLs into the first extension module of the lipomycin PKS (LipPKS1).
• Expanded the method to bimodular communication by introducing RLs into LipPKS2 for triketide lactone production.
• Utilized atom pair chemosimilarity analysis to predict and correlate with product formation.

Main Results:

• Engineered unimodular PKSs achieved product titers correlating with RL substrate similarity to LipPKS1.
• Reached a titer of 165 mg/L of short-chain fatty acids using engineered *Streptomyces albus* J1074.
• Observed a statistically significant correlation between atom pair chemosimilarity and product yield in both unimodular and bimodular PKS engineering.

Conclusions:

• Chemoinformatics provides a powerful and predictive method for engineering PKS reductive loop (RL) exchanges.
• This approach facilitates the production of desired, unnatural polyketide products.
• The established chemoinformatic method can guide the rational design of PKS for novel chemical synthesis.