Abstract
Pulse dipolar EPR spectroscopy (PDS) measurements are an important complementary tool in structural biology and are increasingly applied to macromolecular assemblies implicated in human health and disease at physiological concentrations. This requires ever higher sensitivity, and recent advances have driven PDS measurements into the mid-nanomolar concentration regime, though optimization and acquisition of such measurements remains experimentally demanding and time expensive. One important consideration is that constant-time acquisition represents a hard limit for measurement sensitivity, depending on the maximum measured distance. Determining this distance a priori has been facilitated by machine-learning structure prediction (AlphaFold2 and RoseTTAFold) but is often confounded by non-representative behaviour in frozen solution that may mandate multiple rounds of optimization and acquisition. Herein, we endeavour to simultaneously enhance sensitivity and streamline PDS measurement optimization to one-step by benchmarking a variable-time acquisition RIDME experiment applied to CuII-nitroxide and CuII-CuII model systems. Results demonstrate marked sensitivity improvements of both 5- and 6-pulse variable-time RIDME of between 2- and 5-fold over the constant-time analogues.
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