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

Abstract

We perform Brownian dynamics simulations and Smoluchowski continuum modeling of the bifunctional Plasmodium falciparum dihydrofolate reductase-thymidylate synthase (P. falciparum DHFR-TS) with the objective of understanding the electrostatic channeling of dihydrofolate generated at the TS active site to the DHFR active site. The results of Brownian dynamics simulations and Smoluchowski continuum modeling suggest that compared to Leishmania major DHFR-TS, P. falciparum DHFR-TS has a lower but significant electrostatic-mediated channeling efficiency (?15-25%) at physiological pH (7.0) and ionic strength (150 mM). We also find that removing the electric charges from key basic residues located between the DHFR and TS active sites significantly reduces the channeling efficiency of P. falciparum DHFR-TS. Although several protozoan DHFR-TS enzymes are known to have similar tertiary and quaternary structure, subtle differences in structure, active-site geometry, and charge distribution appear to influence both electrostatic-mediated and proximity-based substrate channeling.

Co-localization and confinement of ecto-nucleotidases modulate extracellular adenosine nucleotide pools

“…In analogy to the effects of the pore charge on ATP, the increased efficiency for positively-charged pores can be rationalized by the pooling of anionic AMP within the pore, which increases k on,AMP . This concurs with our findings of enhanced reaction efficiency in dihydrofolate reductase-thymidylate synthase (DHFR-TS) [21] owing to its complementary surface charge to the dihydrofolate intermediate intermediate, in contrast to a neutral or electrically-repulsive surface. For the co-localized cases at the membrane surface, it is likely that the membrane significantly competed with the binding of B at CD73, which led to a reduced reaction rate coefficient.…”

“…This finding mirrors trends observed in other coupled enzymatic processes; namely in the event that enzymes or reactive sites are sequentially aligned for coupled enzymatic reactions, electrostatic channeling of substrates is commonly exploited in nature to optimize the rate or efficiency of substrate conversion [75, 101, 102]. As an example, a computational study of the DHFR-TS enzyme in prokaryotes has revealed that tetrahydrofolate production rates are accelerated by a patch of positively-charged amino acids between the thymidylate synthase and dihydrofolate reductase reactive sites, which facilitate transfer of the anionic dihydrofolate intermediate [21]. Significantly, when the enzymes’ charges were complementary to those of the reactants, the overall reaction efficiency exceeded predictions for the uncharged, confined enzymes and the enzymes in bulk solution.…”

“…For diffusion-limited reactions, the efficiency of sequentially-coupled reactions is strongly determined by the relative distance between enzymes, as well as the rates of substrate diffusion toward their reactive centers [19]. Further, sequential enzyme reactivity depends on the transfer efficiency of intermediates, which can be facilitated by molecular tunnels [20] or electrostatic channeling [19, 21]. An essential consideration is therefore how intrinsic rates of substrate diffusion in bulk solution are modulated by steric and long-range electrostatic interactions between substrates and target enzymes versus those with the surrounding cellular environment [22, 23].…”

“…These models provided strong quantitative insights into the efficiency of catalytic processes [46] and limits on efficiency gains for sequentially-coupled enzymes [45], but only implicitly account for geometrical and physiochemical factors. Explicit consideration of those factors for coupled enzyme processes generally utilize partial differential equations or particle-based solutions, which have afforded descriptions of how neighboring reactive enzymes [29, 47, 48], feedback inhibition, [29, 46], protein geometry and electrostatic interactions [19, 21, 49, 50] contribute to enzyme activity. Still, a systematic study of sequential reaction phenomena under physiological variations in solvent ionic strength and intracellular confinement is needed for probing how nucleotide pools are regulated by sequential NDAs in geometrically-constrained intercellular junctions.…”

Understanding ligand-receptor non-covalent binding kinetics using molecular modeling

“…SDA has been used extensively for this purpose, and has been modified to accommodate the investigation of protein-DNA and protein-RNA association (130–137). Similarly, BrownDye is designed as general purpose rigid-body bimolecular association rate calculation software, with support for standard and weighted BD simulations, and is capable of lending insight into subtle processes such as substrate channeling (118, 138–140). Also operating under the rigid-body approximation, GeomBD specifically focuses on simulating and characterizing intermediate substrate transfer processes in multi-receptor systems, calculating first-order rate constants for each intermediate transfer step in a series of receptors (141, 142).…”