The minimum and optimal restraints in FRET-assisted protein structural modeling*

While our ability to predict protein x-ray crystal structures has improved dramatically via the application of deep learning, much is still unknown about the effects of cellular environments on protein structure, dynamics, and function. Recently, Forster Resonance Energy Transfer (FRET) has been shown to be an effective tool for probing protein structure in vivo. When combined with all-atom molecular dynamics (MD) simulations, these two techniques can dramatically increase our insight into protein structure in vivo. However, given the large number of possible FRET residue pairs to measure, what is the minimum number of FRET pairs needed to determine a conformational change and what is the optimal method for selecting these FRET pairs? Here, we explore state-of-the-art methods for selecting FRET pairs to determine how many pairs N_r are needed to drive a known conformational change between two x-ray crystal structures. We find that it is possible to induce conformational changes using only a small fraction of restraints, N_r/N, where N is the number of amino acids. These results establish the feasibility of FRET-assisted structural modeling and provide a practical approach to planning FRET experiments.