In a significant stride toward sustainable chemical synthesis, researchers have harnessed the power of artificial intelligence to engineer an enzyme that could revolutionize the production of chiral amines—critical components in both pharmaceuticals and agrochemicals. The study, led by Xiaole Yang of the Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening at Jiangsu Ocean University, was recently published in the journal *Biomolecules*.
Chiral amines are molecules with a “handedness” that dictates their biological activity. In agrochemicals, this enantiomeric purity can mean the difference between an effective crop protection agent and an environmental hazard. Traditional methods of producing these compounds often rely on toxic chemicals and complex processes. However, the newly engineered enzyme offers a greener alternative.
The research team identified a novel (*R*)-selective amine transaminase, dubbed MwoAT, from a strain of *Mycobacterium*. This enzyme naturally synthesizes (*R*)-1-methyl-3-phenylpropylamine, a precursor for the antihypertensive drug dilevalol and a potential scaffold for new agrochemicals. “The enzyme’s high thermostability and solvent tolerance make it an ideal candidate for industrial applications,” Yang explained.
To enhance the enzyme’s efficiency, the researchers employed an AlphaFold3-guided semi-rational engineering strategy. This approach combined molecular docking, alanine scanning, and saturation mutagenesis to pinpoint critical residues for substrate binding. The team zeroed in on residue L175, which, when mutated to glycine (L175G), boosted the enzyme’s catalytic efficiency by 2.1-fold and improved its thermal stability.
The engineered enzyme achieved a 26.4% conversion rate for the synthesis of (*R*)-1-methyl-3-phenylpropylamine with an enantiomeric excess of ≥99.9%. This level of precision is crucial for agrochemical applications, where even trace amounts of the wrong enantiomer can lead to unwanted environmental effects.
Beyond its immediate application, the study demonstrates a versatile framework for AI-assisted protein engineering. “This method can be applied to other enzymes involved in agrochemical synthesis, paving the way for more sustainable and efficient production processes,” Yang noted.
The implications for the agriculture sector are profound. As the demand for environmentally friendly agrochemicals grows, enzymes like MwoAT could become indispensable tools in the chemist’s arsenal. By enabling the precise synthesis of chiral amines, this technology could lead to the development of safer and more effective crop protection agents, ultimately benefiting both farmers and the environment.
This research not only highlights the potential of AI in protein engineering but also underscores the importance of interdisciplinary collaboration in driving agricultural innovation. As the field continues to evolve, such advancements will be crucial in meeting the challenges of sustainable agriculture.