GAO Caixia’s group at the Institute of Gene and Developmental Biology, Chinese Academy of Sciences has pioneered the use of artificial intelligence (AI)-assisted methods to discover novel deaminase proteins with unique functions through structure prediction and classification.
This approach has opened up a wide range of applications for the discovery and creation of desirable plant genetic traits.
The results were published in Cell magazine.
The discovery of new proteins and the utilization of diverse artificial enzymes have contributed to rapid advances in biotechnology. Efforts to unearth novel proteins currently generally rely on amino acid sequences, which cannot provide robust links between protein structural information and function.
Base editing is a novel precision genome editing technique that has the potential to revolutionize molecular crop breeding by introducing desirable traits into elite germplasm. The discovery of several deaminases has expanded the capacity for cytosine base editing. Although traditional sequence-based efforts have identified many proteins that can be used as base editors, there are still limitations to editing specific DNA sequences or species.
Standard approaches based solely on protein engineering and directed evolution have helped diversify base-editing properties, but challenges remain. Using AlphaFold2 to predict the structure of proteins within the deaminase protein family, researchers clustered and analyzed deaminases based on structural similarity. They identified five new deaminase clusters with cytidine deamination activity from the perspective of DNA base editors.
Using this approach, they further reclassified a group of cytidine deaminases previously thought to act on dsDNA, called SCP1.201, and deaminate primarily on ssDNA. Through subsequent protein profiling and engineering efforts, we have developed a series of novel DNA-based editors with remarkable features. These deaminases exhibit properties such as higher efficiency, fewer occurrences of off-target editing events, editing at different preferred sequence motifs, and much smaller size.
The researchers emphasized that the development of a set of basic editors will enable customized applications for different therapeutics and agro-breeding efforts in the future. They developed a minimal single-strand-specific cytidine deaminase, allowing the first efficient cytosine base editor to be packaged into a single adeno-associated virus.
They also found a highly effective deaminase from this clade, specifically in soybean plants, a globally important crop that had previously exhibited poor editing by cytosine base editors.
In general, the recent advent of protein structure prediction using growing genomic databases will greatly accelerate the development of new bioengineering tools.
This study focuses on developing a series of new technologies using only the cytidine deaminase superfamily and an approach to reveal new protein functions. These newly discovered deaminases, based on AI-assisted structural predictions, greatly expand the utility of base editors in therapeutic and agricultural applications.
Moreover, this work will be of broad interest to the larger research community in phylogeny, metagenomics, protein engineering and evolution, genome editing, and plant breeding.
The research was supported by the National Natural Science Foundation of China, the National Key Research and Development Program of China, the Agriculture and Rural Affairs of China, and others.
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