A model study of sequential enzyme reactions and electrostatic channeling

Abstract

We study models of two sequential enzyme-catalyzed reactions as a basic functional building block for coupled biochemical networks. We investigate the influence of enzyme distributions and long-range molecular interactions on reaction kinetics, which have been exploited in biological systems to maximize metabolic efficiency and signaling effects. Specifically, we examine how the maximal rate of product generation in a series of sequential reactions is dependent on the enzyme distribution and the electrostatic composition of its participant enzymes and substrates. We find that close proximity between enzymes does not guarantee optimal reaction rates, as the benefit of decreasing enzyme separation is countered by the volume excluded by adjacent enzymes. We further quantify the extent to which the electrostatic potential increases the efficiency of transferring substrate between enzymes, which supports the existence of electrostatic channeling in nature. Here, a major finding is that the role of attractive electrostatic interactions in confining intermediate substrates in the vicinity of the enzymes can contribute more to net reactive throughput than the directional properties of the electrostatic fields. These findings shed light on the interplay of long-range interactions and enzyme distributions in coupled enzyme-catalyzed reactions, and their influence on signaling in biological systems.

Predicting the influence of long-range molecular interactions on macroscopic-scale diffusion by homogenization of the Smoluchowski equation

“…Since more particles are available to diffuse from the higher concentration side toward the attractor in the cell interior, a net flux due to the attractive interaction may be observed. In support of this interpretation, in a previous study 34 we considered an analogous configuration, in which diffusion of an anionic reaction intermediate between two positively charged reaction centers was modeled. In that model, one reaction center produced an intermediate while the other absorbed the intermediate, yielding a concentration gradient at steady-state.…”

Electrostatic Channeling in P. falciparum DHFR-TS: Brownian Dynamics and Smoluchowski Modeling

“…Whereas Brownian dynamics simulations are useful for tracking the motion of individual particles, the continuum model is convenient for calculating probabilities (ensemble-averaged quantities) such as the steady-state intermediate concentration distribution on the solvent-accessible surface of an enzyme. The major difference between these methods comes from the fact that Brownian dynamics is based on the Langevin equation and the continuum model is based on the Smoluchowski equation (4,14,15). The equivalence of the two approaches within certain limits is well established (16).…”

“…More precisely, substrate channeling refers to the scenario where an intermediate from one reaction site is transferred to a consecutive reaction site without complete mixing of the intermediate with the bulk solvent (3). This efficient transfer can be achieved through molecular tunnels, electrostatic channeling, or active sites in close proximity (3,4). Although a molecular tunnel relies on the geometric confinement of intermediates to prevent their diffusion into bulk solvent, electrostatic-mediated substrate channeling utilizes electrostatic interactions to create a virtual tunnel that confines the intermediate between the two reaction sites (4,5).…”

Enzyme localization, crowding, and buffers collectively modulate diffusion-influenced signal transduction: Insights from continuum diffusion modeling

“…[1][2][3] Recently, we quantified the impact of crowding and competition on a substrate/enzyme association rate 4 as well as the impact of proximity and electrostatic interactions on reaction rates in coupled enzyme systems. 5 In the first study, we found that the density of off-target crowders greatly attenuated the substrate association rate, which was not unexpected given the inverse relationship between effective diffusion coefficients and the accessible volume fraction 6,7 (see also Figure 1(a) and Fig. 3 of Ref.…”

“…Moreover, we demonstrated that competitive binding of substrate by these crowders further reduced the effective reaction rate in a non-linear fashion, in a manner analogous to strongly buffered systems, where the effective diffusion coefficient may be significantly attenuated depending on the buffer concentration, equilibrium constant, and diffusivity. 9 In the second study, 5 we quantified the competition between the proximity of two enzymes participating in a sequential set of reactions, electrostatic interactions between a diffuser and the enzymes or crowders, and the volume excluded by those enzymes (see Figure 1(b)). We found that the evolution of product could be accelerated by favorable electrostatic interactions between a substrate and the enzyme at which it is consumed, or by lining a channel between enzymes with charges complementary to the intermediate, similar to electrostatic channeling observed between active sites in bifunctional enzymes.…”