It is increasingly apparent that dynamic motions can be equally important as structure in biomolecular mechanisms of action. Structures of 70,000 proteins have been determined experimentally, but the dynamics of only a handful have been mapped comprehensively. Emerging developments in NMR spectroscopy are making it possible, in favorable cases, to characterize dynamics over a broad range of functionally-relevant time regimes. Arginine kinase has been developed as a model system, amenable to the several techniques necessary, to characterize the conformational dynamics of a representative metabolic enzyme. It will be used to elucidate the interplay of intrinsic and substrate-induced motions at critical points in the catalytic cycle and to understand how protein dynamics can limit enzymatic turnover rate. Arginine kinase (AK) is an attractive model enzyme because it catalyzes a phosphoryl transfer reaction with a millisecond turnover rate that is limited by conformational dynamics. At 42 kDa, it is larger than previously characterized systems and exhibits a rich repertoire of domain rotations and loop motions. Crystal structures at atomic resolution will be combined with dynamics from several types of NMR to build a structure-dynamic model spanning the pico-second through millisecond regimes. AK presents an excellent opportunity to investigate near-native protein dynamics of the transition state (TS), because its TS analog, unlike the bisubstrate complexes used for most bimolecular enzymes, is free from artificial covalent constraints.
Aim 1 will extend our dynamics characterization from substrate-free enzyme to a transition state analog complexes, using NMR relaxation dispersion, residual dipolar coupling and spin-spin relaxation. This will reveal changes in backbone motions as the enzyme progresses through the catalytic cycle, and the interplay of fast and slow dynamics.
Aim 2 will develop computer algorithms for optimization of structure-dynamics models. Methods will support holistic integration of complementary data from diverse crystallographic and NMR experiments.
Aim 3 will determine the functional role of each motion. Variation in the NMR relaxation exchange of reacting enzyme with substrate concentration will distinguish motions required for binding or dissociation from those important in chemical steps. Our experimental analysis will inform current theoretical debate about the roles of induced-fit, conformational selection and transition state stabilization in protein motions. It will determine the extent of links between fast and slow dynamics, elucidate the coordination of different motions in a large protein, and reveal how enzymes achieve precise substrate alignment while undergoing large conformational changes. The project will have broad impact in basic biochemistry and build the foundations for understanding the molecular basis of disease.
Protein structure has been a critical part of understanding the molecular basis of disease, but it is increasingly appreciated that function and mechanism are intimately associated with motions that go beyond the static images available from standard approaches. Here, high resolution crystallography, emerging nuclear magnetic resonance methods and enzyme kinetics will be applied to a model enzyme that is representative of many important metabolic reactions, to elucidate how motions over wide, pico- to millisecond time regimes, are coordinated through the enzyme reaction cycle. Characterization of the dynamics will be an advance in basic biochemistry, informing our view of normal mechanism, and providing insights as to how, in principle, molecular pathologies could be caused by perturbed dynamics.
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