Demonstrating the Potential to Minimize Side Effects and Maximize Efficacy Through Precision Design
Galaxy, an AI-driven drug discovery company, announced on September 22 that it has achieved antibody design results for eight therapeutic targets using its proprietary protein design platform, "Galaxy Design."
According to Galaxy, these results further demonstrate the scalability and precision of its platform, following the announcement in March of de novo antibody design results for six targets. This report covers successful antibody design cases for a total of eight target proteins: PD-L1, HER2, EGFR (S468R), ACVR2A/B, FZD7, ALK7, CD98hc, and IL-11.
In particular, the company succeeded in designing antibodies for the anti-aging target IL-11, which previously had no known antigen-antibody structural information, proving that the platform can create entirely novel antibodies. For IL-11, Galaxy was also able to generate antibodies that act on various binding sites, demonstrating the ability to design functional diversity as well.
It was also reported that antibodies that showed binding to target proteins in their initial fragment form (scFv) maintained high binding affinity and stability even in their full antibody form (IgG). For the EGFR-S468R and FZD7 targets, Galaxy succeeded in designing antibodies that can distinguish between specific mutations or similar proteins with only one or two amino acid differences, enabling precise binding to the intended targets.
These results demonstrate that Galaxy Design can be used to create next-generation precision antibodies that maximize efficacy while minimizing side effects. A particularly notable achievement is the structural validation of the designed PD-L1 antibody. Cryo-EM analysis of the binding structure between PD-L1 and the antibody revealed that the AI-designed antibody (GX-aPDL1-3) binds in a manner distinct from any previously reported PD-L1 antibodies, and that the experimentally determined structure matches the intended model at the atomic level (iRMSD 1.1A).
Antibodies are key tools in the development of therapeutics targeting various diseases. However, traditional development methods have relied on animal immune responses or large-scale library screening, which are time-consuming and have low success rates in securing the desired precision antibodies. This study is significant in showing that AI can overcome these limitations.
Galaxy CEO Seok Chaok stated, "Our technology maximizes efficacy and reduces side effects by enabling the design of precision therapeutics at the early stages of drug development, thereby increasing the success rate of subsequent development stages and greatly improving overall drug development efficiency. We are entering an era where drugs are no longer discovered by chance, but are precisely designed according to purpose and intent."
Galaxy is currently expanding its antibody design research to target proteins, such as GPCRs and ion channels, which have been difficult to approach with traditional antibody discovery methods. The company is also accelerating research and development through collaborations with various domestic and international pharmaceutical companies, aiming to rapidly advance AI-designed precision antibodies into clinical stages.
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