PROJECT SUMMARY/ABSTRACT This project develops new experimental and computational methods for DEER (double electron- electron resonance) spectroscopy. DEER is a biostructural technique for the quantification of protein conformational landscapes and protein motions on the nanometer scale. Protein motions are crucial for many key molecular processes at the basis of human life and disease. Therefore, DEER provides important insights that contribute to the knowledge base necessary for drug development. In combination with X-ray crystallography, cryo-EM, NMR, FRET and others, DEER is part of a complementary set of integrative experimental biostructural tools. It is especially important for the study of membrane proteins. Several major barriers exist in the field: the lack of integrated analysis and modeling tools for biomedical researchers, and the lack of experimental approaches for studying proteins in their native cellular environment. This project directly addresses these issues as it aims to (a) develop methods and tools based on Bayesian statistics and deep learning for the rigorous and reproducible analysis of experimental DEER data; (b) create advanced computational approaches that utilize DEER data for modeling proteins; (c) develop methodology based on noncanonical amino acids for labeling proteins directly in their cellular environment; (d) advance a rapid freeze quench approach to measure conformational dynamics down to the sub-millisecond time scale. Overall, the goal of the project is to significantly expand the scope of DEER by providing innovative approaches to data analysis, modeling, and in-cell and time-resolved measurements. This will enable the study of the structure and dynamics of larger and more complex proteins and protein assemblies in the cellular environment. This is of increasing importance in biomedical research.