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

A comprehensive review of lipase-catalyzed acidolysis as a method for producing structured glycerides

The production of structured lipids is a current trend in food technology in order to enhance the properties of fats and oils. Lipases have been utilized in many instances for this purpose, in most examples in an immobilized form. In this review, after discussing the different strategies to produce artificial lipids using lipases (esterification, transesterification, interesterification), we have focused on acidolysis. The reaction commences with hydrolysis at one position of the triglyceride molecule and is followed by the esterification between the released hydroxyl group and the target fatty acid (although other carboxylic acids can be used, such as phenolic acid derivatives). This means that water plays a double role, as substrate in the first step and as an undesired by-product in the second one. Therefore, the control of water activity becomes critical in these reactions. This review discusses the advantages, possibilities and drawbacks of this strategy to produce tailor-made designed lipids, summarizing many of the papers related to this strategy. The summarized results show the complexity of this reaction that can make the understanding and reproducibility of the reactions complex if there are no strict controls of all parameters determining the final yields.

Computer-Aided Design to Improve the Thermal Stability of Rhizomucor miehei Lipase

Lipase, a green biocatalyst, finds extensive application in the food sector. Enhancing the thermal stability of lipase presents both challenges and opportunities within the food industry. This research employed multiple rounds of cross-screening using tools like FoldX and I-Mutant 3.0 to strategically design mutations for Rhizomucor miehei lipase (RML), resulting in eight unique single-point mutation designs. E230I, N120M, and N264M have been confirmed experimentally to be potential combination mutation candidates. The resulting triple mutant N120M/E230I/N264M showed a higher thermal stability, with an optimum temperature of 55 °C, 10 °C higher than that of the wild-type RML. The half-life was extended from 46 to 462 min at 50 °C. Furthermore, the catalytic activity of N120M/E230I/N264M on camphor tree seed oil increased by 140% to 600 U/mg, which aids in the production of novel structured lipids. Using molecular docking and molecular dynamics simulations, we analyzed the molecular mechanism of enhanced thermal stability. This study validated the efficacy and dependability of computer-aided design to generate heat-resistant RML mutants and indicated that RML N120M/E230I/N264M lipase can be used as an effective biocatalyst for fat processing in the food industry.

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.