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Revolutionary studies: now controlling enzymes with light!
Scientists from the University of Regensburg present an innovative study on enzymatic catalysis and its application in industry.
Revolutionary studies: now controlling enzymes with light!
Scientist of the University of Regensburg have published a groundbreaking study on the precise spatiotemporal control of biochemical transformations. This research illuminates the role of enzymes as biocatalysts that accelerate cellular reactions and convert substrates into products.
Enzymes that consist of amino acids show a structure-dependent functionality that is determined by the respective sequence of amino acids. The active center of an enzyme is particularly crucial, as it enables both substrate binding and catalysis. Interestingly, substrates can exist in two enantiomeric forms, with enzymes typically exhibiting enantioselectivity.
Innovative modification through protein engineering
A central point of the study is that enzymes are suitable for industrial and medical applications, but often require targeted modifications. This is where protein engineering comes into play, allowing the exchange of amino acids to optimize enzyme activity. The latest techniques in this field allow the use of unnatural amino acids (UAS) in cells. These photo-sensitive UAS can be strategically incorporated into the active sites of enzymes to control their activity.
The study specifically examines the enzyme phosphotriesterase (PTE), which is capable of converting toxic substrates into non-toxic products. By UV irradiation of an enzyme modified with a photosensitive amino acid, the enantioselectivity could be changed, which made it possible to bind and convert a different enantiomer.
Latest research results and their effects
The results are based on a bioinformatic analysis of the spatial structure of the PTE and the corresponding changes in the active site. This research opens up new opportunities for the pharmaceutical-chemical industry. This study was carried out in close cooperation between Prof. Reinhard Sterner, Prof. Till Rudack from the University of Regensburg and Prof. Frank Raushel from Texas A&M University. The original publication was published in the journal JACS Au under the title “Photo-Controlling the Enantioselectivity of a Phosphotriesterase via Incorporation of a Light-Responsive Unnatural Amino Acid”.
At the same time, a team of researchers is developing Jülich Research Center new methods based on existing deep learning algorithms. These are aimed at improving prediction in enzyme engineering and enzyme functional classification. The group maintains the TopEC project, an improved enzyme functional classification framework based on the TopEnzyme database.
The focus of this research is the use of 3D graph convolutional neural networks to precisely predict substitution effects on enzyme activity and stability. The implementation of structural and sequence-based features within these networks aims to increase the stability of proteins and improve enzyme functional classification.
The exciting synergy between biochemical theory and modern technologies not only promises advances in basic research, but could also have far-reaching implications for industrial applications in enzyme research.