AI-guided protein design for new anti-inflammatory therapeutics

Machine-learning design of new cytokine receptor modulators Cytokines are small immune signalling proteins that control inflammation, but many are difficult to develop directly as medicines because they can be unstable, short-lived in the body, or hard to manufacture. This project will use machine-learning-based protein design to create new small protein binders that target receptors from the IL-1 cytokine family, an important group of immune receptors involved in inflammatory disease. The goal is to design binders that can either activate or block selected cytokine receptor complexes, creating potential agonists or antagonists with therapeutic applications. The project will combine computational protein design with experimental validation. Students may help design and prioritise binder libraries, express and purify candidate proteins, test receptor binding, and structurally characterise promising designs using biochemical and structural biology approaches. Lead binders may also be formatted as Fc-fusion proteins to improve stability and enable functional testing. This project is suited to students interested in protein engineering, immunology, structural biology and next-generation biologic therapeutics.