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Electrostatic interactions are known experimentally to enhance the rate of protein-protein association by three to four orders of magnitude. However, theoretical efforts to quantitatively account for such rate enhancement have been hampered by the need to consider a large number of relative configurations of two associating proteins sampled during their diffusional encounter. Our recent work indicates that a good estimate of the rate enhancement is given by the average Boltzmann factor in the region of configurational space where association can effectively take place. This estimate is tested on a model system consisting of two spherical proteins, each with a "reactive patch." Three different forms of interaction potential are considered. Comparison with exact results for the association rate constant demonstrates that predictions based on the local Boltzmann factor are accurate to within approximately 50% for realistic sizes of the reactive region and amplitudes of the interaction potential.

A general formalism is developed for calculating the time-dependent rate coefficient k(t) of an irreversible diffusion-influenced reaction. This formalism allows one to treat most factors that affect k(t), including rotational Brownian motion and conformational gating of reactant molecules and orientation constraint for product formation. At long times k(t) is shown to have the asymptotic expansion k(infinity)[1 + k(infinity) (pie Dt)-1/2 /4 pie D + ...], where D is the relative translational diffusion constant. An approximate analytical method for calculating k(t) is presented. This is based on the approximation that the probability density of the reactant pair in the reactive region keeps the equilibrium distribution but with a decreasing amplitude. The rate coefficient then is determined by the Green function in the absence of chemical reaction. Within the framework of this approximation, two general relations are obtained. The first relation allows the rate coefficient for an arbitrary amplitude of the reactivity to be found if the rate coefficient for one amplitude of the reactivity is known. The second relation allows the rate coefficient in the presence of conformational gating to be found from that in the absence of conformational gating. The ratio k(t)/k(0) is shown to be the survival probability of the reactant pair at time t starting from an initial distribution that is localized in the reactive region. This relation forms the basis of the calculation of k(t) through Brownian dynamics simulations. Two simulation procedures involving the propagation of nonreactive trajectories initiated only from the reactive region are described and illustrated on a model system. Both analytical and simulation results demonstrate the accuracy of the equilibrium-distribution approximation method.

A general method for calculating translational friction and intrinsic viscosity is developed through exploiting relations between hydrodynamics and electrostatics. An approximate relation xi = 6 pi eta 0C between the translational friction coefficient xi of a particle (eta 0: solvent viscosity) and its capacitance C was derived previously. This involved orientationally preaveraging the Oseen tensor, but the result was found to be very accurate. Based on preaveraging, we find that the intrinsic viscosity [eta] of a particle can be estimated from its polarizability alpha through [eta] = 3/4 alpha + 1/4 Vp, where Vp is the volume of the particle. Both the capacitance and the polarizability can be obtained in a single calculation using the boundary-element technique. An efficient approach is thus found for estimating [eta], a quantity that is very useful in practice because of its sensitivity to particle shape but is notoriously difficult to calculate. Illustrative calculations on ellipsoids, cylinders, and dumbbells demonstrate both the accuracy of the approximate relations and the efficiency of the present method.

The boundary element technique is implemented to solve for the electrostatic potential of macromolecules in an ionic solution. This technique entails solving surface integral equations that are equivalent to the Poisson and the Poisson-Boltzmann equations governing the electrostatic potential inside the macromolecules and and in the solvent. A simple but robust method is described for discretizing the macromolecular surfaces in order to approximate the integral equations by linear algebraic equations. Particular attention is paid to the interaction energy between two macromolecules, and an iterative procedure is devised to make the calculation more efficient. This iterative procedure is illustrated in the electron transfer system of cytochrome c and cytochrome c peroxidase.

A unified model is presented for protein-protein association processes that are under the influences of electrostatic interaction and diffusion (e.g., protein oligomerization, enzyme catalysis, electron and energy transfer). The proteins are modeled as spheres that bear point charges and undergo translational and rotational Brownian motion. Before association can occur the two spheres have to be aligned properly to form a reaction complex via diffusion. The reaction complex can either go on to form the product or it can dissociate into the separate reactants through diffusion. The electrostatic interaction, like diffusion, influences every step except the one that brings the reaction complex into the product. The interaction potential is obtained by extending the Kirkwood-Tanford protein model (Tanford, C., and J. G. Kirkwood. 1957. J. Am. Chem. Soc. 79:5333-5339) to two charge-embedded spheres and solving the consequent equations under a particular basis set. The time-dependent association rate coefficient is then obtained through Brownian dynamics simulations according an algorithm developed earlier (Zhou, H.-X. 1990. J. Phys. Chem. 94:8794-8800). This method is applied to a model system of the cytochrome c and cytochrome c peroxidase association process and the results confirm the experimental dependence of the association rate constant on the solution ionic strength. An important conclusion drawn from this study is that when the product is formed by very specific alignment of the reactants, as is often the case, the effect of the interaction potential is simply to scale the association rate constant by a Boltzmann factor. This explains why mutations in the interface of the reaction complex have strong influences on the association rate constant whereas those away from the interface have minimal effects. It comes about because the former mutations change the interaction potential of the reaction complex significantly and the latter ones do not.

We have generalized the double nucleation mechanism of Ferrone et al. (Ferrone, F. A., J. Hofrichter, H. Sunshine, and W. A. Eaton. 1980. Biophys. J. 32:361-377; Ferrone, F. A., J. Hofrichter, and W. A. Eaton. 1985. J. Mol. Biol. 183:611-631) to describe the spatial dependence of the radial growth of polymer domains of sickle hemoglobin. Although this extended model requires the consideration of effects such as monomer diffusion, which are irrelevant to a spatially uniform description, no new adjustable parameters are required because diffusion constants are known independently. We find that monomer diffusion into the growing domain can keep the net unpolymerized monomer concentration approximately constant, and in that limit we present an analytic solution of the model. The model shows the features reported by Basak, S., F. A. Ferrone, and J. T. Wang (1988. Biophys J. 54:829-843) and provides a new means of determining the rate of polymer growth. When spatially integrated, the model exhibits the exponential growth seen in previous studies, although molecular parameters derived from analysis of the kinetics assuming uniformity must be modified in some cases to account for the spatially nonuniform growth. The model developed here can be easily adapted to any spatially dependent polymerization process.