De novo enzyme design: Controlling structure to design function.

Area of Science:

• Biochemistry
• Enzyme Engineering
• Computational Chemistry

Background:

• De novo enzyme design seeks to create novel enzymes with natural-like efficiency and versatility.
• Historically, design methods produced enzymes with low catalytic efficiency, necessitating improved control over protein structure and active site organization.
• Challenges remain in achieving high catalytic rates and complex, multistep mechanisms for designed enzymes.

Purpose of the Study:

• To review recent advancements in de novo enzyme design methodologies.
• To highlight emerging strategies like AI-driven design and evolution-guided atomistic design.
• To identify key challenges and future directions for developing high-performance enzymes.

Main Methods:

• Artificial intelligence-driven design of novel protein folds.
• Evolution-guided atomistic design applied to natural protein folds.
• Analysis of strategies for controlling backbone structure and active-site preorganization.

Main Results:

• Emerging strategies have yielded catalysts with efficiencies approaching those of natural enzymes.
• Significant progress has been made in designing enzymes for specific reactions.
• High catalytic rates and complex, multistep mechanisms remain areas for further development.

Conclusions:

• Progress in de novo enzyme design requires precise control over complex natural protein folds.
• Close collaboration between enzyme designers and computational chemists is crucial.
• Future efforts should focus on enhancing catalytic rates and enabling complex enzymatic mechanisms for novel reactions.