Project Summary/Abstract Protein-protein interactions (PPIs) are involved in a diverse array of critical biological processes, including cell proliferation, growth, differentiation, and apoptosis. To date, there is no general way to modulate collagen protein-protein interactions, and many fundamental aspects of biomolecular recognition are still unknown. Specifically, numerous interactions between collagen triple helices and proteins are not fully characterized or understood. We have recently shown that collagen aza-peptides in which at least one alpha-carbon atom has been substituted with nitrogen, have additional interstrand hydrogen bonds in their collagen triple helix, resulting in hyperstability and more efficient self-assembly. As a result, even short collagen aza-peptides reliably self-assemble into thermostable triple helices, making them a promising choice for novel triple helix mimics. With this project, we propose to use minimal aza-peptides to create linear and cyclic collagen peptide triple helix mimics. Our specific aims are as follows: 1) Synthesize and characterize hyperstable synthetic mimics of collagen peptides; 2) Synthesize and characterize cyclic collagen peptide triple helix mimics (CCP-mimics); 3) Characterize protein interactions our synthetic collagen peptides. Aza-peptides will be synthesized using solid-phase peptide synthesis (SPPS) in order to introduce aza-amino acids into the collagen backbone at precise locations and optimize thermodynamic stability of the linear and cyclic peptides. The modular nature of our new collagen peptide systems will provide highly tunable platforms into which any biologically relevant protein binding sequence can be integrated. Our collagen peptide mimics will serve as new chemical tools for understanding the fundamental biology and biochemistry of the collagen-protein interactome. The proposed studies could ultimately serve as the fundamental science leading to future biomedical treatments for pathologies in which precisely modulating collagen-protein interactions could significantly enhance patient outcome.