Artificial Intelligence Aided Lipase Production and Engineering for Enzymatic Performance Improvement.

Area of Science:

• Biotechnology
• Enzyme Engineering
• Artificial Intelligence Applications

Background:

• Artificial intelligence (AI) is revolutionizing enzyme engineering, offering advanced methods for optimizing enzyme production and characteristics.
• AI-driven protocols, particularly optimized network models, are increasingly used to predict and enhance lipase production, catalytic activity, stability, and substrate specificity.

Purpose of the Study:

• To review AI-based network models and algorithms for predicting and modifying lipase properties and production.
• To analyze the advantages and disadvantages of various AI approaches in lipase engineering.
• To identify research gaps and future perspectives for AI in enzyme engineering, focusing on lipase.

Main Methods:

• Review of different neural network models and algorithms applied to lipase production and property prediction.
• Analysis of AI applications in modifying lipase molecules and structures.
• Discussion of AI's role in optimizing cultivation for lipase yield.

Main Results:

• AI effectively predicts lipase yield and properties by optimizing cultivation and analyzing molecular variations.
• Current AI applications primarily focus on optimizing production and predicting property changes, with limited direct enzyme structure engineering.
• Significant research gaps exist in directly using AI to engineer lipase structure for enhanced function.

Conclusions:

• AI offers powerful tools for optimizing lipase production and engineering, with potential for significant industrial applications.
• Further research is needed to explore AI's direct role in enzyme structural modification for novel biocatalyst design.
• AI advancements are crucial for developing innovative biocatalysts for the food industry and biomass conversion.