Computer-Aided Lipase Engineering for Improving Their Stability and Activity in the Food Industry: State of the Art

Enzyme Engineering: Performance Optimization, Novel Sources, and Applications in the Food Industry

This review summarizes the latest progress in enzyme preparation, including enzyme design and modification technology, exploration of new enzyme sources, and application of enzyme preparation in food processing, detection, and preservation. The directed evolution technology improved the stability and catalytic efficiency of enzymes, while enzyme immobilization technology enhanced reusability and industrial applicability. Extremozymes and biomimetic enzymes exhibit excellent performance under harsh conditions. In food processing, enzyme preparation can improve food quality and flavor. In food detection, enzymes combined with immune detection and biosensors realize rapid detection of allergens, pollutants, and pesticide residues. In food preservation, enzymes enhance food quality by extending shelf life and inhibiting microbial growth. In the future, enzyme engineering will be combined with computer-aided design, artificial intelligence, and new material technology to promote intelligent enzyme design and multifunctional enzyme preparation development and help the technological upgrading and sustainable development of the food industry and green chemistry.

Deep learning-based characterization and redesign of major potato tuber storage protein

Potato is one of the most important crops worldwide, to feed a fast-growing population. In addition to providing energy, fiber, vitamins, and minerals, potato storage proteins are considered as one of the most valuable sources of non-animal proteins due to their high essential amino acid (EAA) index. However, low tuber protein content and limited knowledge about potato storage proteins restrict their widespread utilization in the food industry. Here, we report a proof-of-concept study, using deep learning-based protein design tools, to characterize the biological and chemical characteristics of patatins, the major potato storage proteins. This knowledge was then employed to design multiple cysteines on the patatin surface to build polymers linked by disulfide bonds, which significantly improved viscidity and nutrient of potato flour dough. Our study shows that deep learning-based protein design strategies are efficient to characterize and to create novel proteins for future food sources.