Generative models for protein design and gene therapy

Gene therapy, which involves delivering therapeutic nucleic acids into cells or correcting defective genes through genetic engineering, holds the potential to revolutionize medical treatment. It offers new hope for treating or even curing diseases that were previously considered incurable or untreatable. Gene therapy, which involves delivering therapeutic nucleic acids into the cell or correcting defective genes through gene engineering, holds the potential to revolutionize medical treatment. It offers new hope for treating or even curing diseases that were previously considered incurable or untreatable. Generative machine learning methods for protein design has introduced new and powerful techniques to the field of protein design and opened new avenues to design virus capsids and nucleic acid constructs. This research theme focuses on using advanced computational modeling and machine learning models to generate proteins with a particular focus on either capsid design or protein design for genetic central nervous diseases.

This research will closely align with the experimental activities of our team at the Center for Integrative Neuroplasticity. Following in silico validation, the designed proteins will undergo functional and gene therapeutic testing in specialized laboratory experiments conducted by other group members. The strong integration between computational and experimental efforts fosters a dynamic and stimulating scientific environment, enhancing collaborative progress and innovation.