Macrocyclic Peptides for C5aR1: Using ML, Physics-Based Methods, and Experimental Verification

This master’s thesis explores the design of macrocyclic peptides targeting the G-protein coupled receptor C5aR1 using advanced computational tools such as Rosetta and RFdiffusion, combined with physics-based modeling and experimental synthesis. The study demonstrates a design-science approach to molecular therapeutics, aiming for inverse agonism through selective anchor interaction. A full computational pipeline and synthesis strategy are presented.