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Guanylate kinase, induced fit, and the allosteric spring probe
Authors:Choi Brian  Zocchi Giovanni
Institution:Department of Physics and Astronomy, University of California, Los Angeles, California
Abstract:Since the introduction of the induced-fit theory by D. E. Koshland Jr., it has been established that conformational motion invariably accompanies the execution of protein function. The catalytic activity of kinases, specifically, is associated with large conformational changes (∼1 nm amplitude). In the case of guanylate kinase, upon substrate binding, the LID and nucleotide-monophosphate-binding domains are brought together and toward the CORE with large concerted movements about the α3 (helix 3) axis. However, whether the change in conformation mostly affects the catalytic rate or mostly increases binding affinities for one or the other substrate is unclear. We investigate this question using a nanotechnology approach based on mechanical stress. Using an “allosteric spring probe”, we bias conformational states in favor of the “open” (substrate-free) conformation of the enzyme; the result is that the binding constant for the substrate guanosine monophosphate (GMP) is reduced by up to a factor of 10, whereas the binding constant for adenosine triphosphate (ATP) and the catalytic rate are essentially unaffected. The results show that the GMP-induced conformational change, which promotes catalysis, does not promote ATP binding, consistent with previous mutagenesis studies. Furthermore, they show that this conformational change is of the induced-fit type with respect to GMP binding (but not ATP binding). We elaborate on this point by proposing a quantitative criterion for the classification of conformational changes with respect to the induced-fit theory. More generally, these results show that the allosteric spring probe can be used to affect enzymatic activity in a continuously controlled manner, and also to affect specific steps of the reaction mechanism while leaving others unaffected. It is presumed that this will enable informative comparisons with the results of future molecular dynamics or statistical mechanics computations.
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