CHEMICALLY-CONTROLLED REACTION KINETICS ON FRACTALS: APPLICATION TO HYDROGEN EXCHANGE IN LYSOZYME
The effect of time-dependent diffusional rate constants on chemically-controlled reactions in solution is considered. A general mechanism is examined that consists of a two step process. First the reactants diffuse together to form an “encounter complex.” This is followed by the collapse of the complex to the final product. The first step is diffusion controlled and the second step is chemically controlled. For reactions in restricted geometries or on fractals the rate constants associated with the diffusive process will scale with time as t−h where h is a constant between 0 and 1. The chemical processes are assumed to have time-independent rate constants. For reactions in which the encounter complex achieves a steady state, the differential equations governing the time course of the reaction can be solved exactly. At short times, the concentration of the reactants decays exponentially, reflecting the time constant of the chemical processes. At longer times, the decreasing diffusive rate constants result in the process being diffusion controlled. A stretched exponential of the form, exp{−kt1−h}, is observed. Approximate solutions for the pre-steady state behavior of the system are also determined using a Liouville transformation and corresponding asymptotic expansions. The short time regime shows power law decays of reactants. These decays will depend both on the dimensionality of the system as well as on the value of the rate constants associated with individual steps in the mechanism. Conditions can exist where a transformation to logarithmic oscillations will occur. Using this theoretical foundation a model is developed to analyze the kinetics of hydrogen isotope exchange kinetics in proteins. The exchange reaction is assume to occur in the boundary volume of the protein. Using the predicted fractal dimension of this boundary volume, scaling exponents are calculated and used as an unadjusted parameter. Highly accurate fits to the experimental data are achieved and activation energies are obtained that reflect the energetics of isotope exchange. This approach allows chemical kinetic behavior to be predicted from X-ray structure information.