A joint research team led by Professor Daesik Kim from Sungkyunkwan University, together with Professor Yong-Sub Kim of the University of Ulsan College of Medicine and Professor Jae-Hyun Park from Sungkyunkwan University School of Medicine, announced on July 30 the development of 'OpenABE' (Open Adenine Base Editor), a next-generation gene editing tool. The team said they achieved this advancement by applying structure-guided protein engineering to AI-derived base editors, resulting in gene editing efficiency improvements of up to 36 times compared to previous models.
Adenine Base Editors are biotechnological tools that locate and correct incorrect adenine bases within DNA sequences. Recent efforts have focused on using artificial intelligence to design novel gene editors not found in nature, but early AI-created models suffered from low efficiency and frequent off-target effects. These issues limited their suitability for clinical applications due to unintended genetic changes outside the target site.
The researchers used AlphaFold-based predictions to analyze the three-dimensional structure of base editors. By identifying key regions that help maintain a strong hold on target DNA, they introduced specific mutations and added a specialized tail structure derived from high-performing conventional base editors. The resulting versions, 'OpenABE 1.1' and 'OpenABE 1.2', demonstrated editing capabilities between 16 and 36 times stronger than existing AI-designed gene editors—performance comparable to ABE8e, which is widely used in laboratories worldwide.
In addition to improved efficiency, the new OpenABE models significantly reduced off-target effects near target genes. The study also showed that precise editing could be performed not only in nuclear DNA but also in mitochondrial DNA—a challenging area due to its unique structure. Delivery methods using engineered virus-like particles allowed for selective targeting with high safety standards.
Professor Daesik Kim said, "This study represents a landmark innovation where human scientists overcame the limitations of early AI-designed gene editors using structure-guided protein engineering. By opening a path to safely cure the causes of genetic diseases in both the nucleus and mitochondria, we expect this work to significantly accelerate the development of therapeutics for genetic disorders." The findings were published in an international journal specializing in genetics and molecular biology.
The research team also recently introduced 'OpenCRISPR-1', another next-generation editor designed by AI that maintains efficiency similar to Cas9 while reducing off-target mutations by up to 553 times. When applied with prime editing technology and virus-like particle delivery systems, OpenCRISPR-1 showed potential as part of an advanced platform for future gene therapies.
