br Methods To study electrostatic substrate

Methods To study electrostatic substrate channeling, we employed two methodologies, Brownian dynamics and a continuum model based on the Smoluchowski theory. 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). Since each approach has its own advantages, we use both methodologies in this study of substrate channeling in P. falciparum DHFR-TS. Below, we describe the preparation of the molecular structures used in either the Brownian dynamics simulations or the continuum model. Details of each approach are also summarized below.
Results and Discussion
Summary and Conclusions By performing Brownian dynamics simulations as well as Smoluchowski continuum modeling, we estimate the predicted transfer efficiency of dihydrofolate in P. falciparum DHFR-TS with electrostatic-mediated and proximity-mediated substrate channeling. Furthermore, we identify the crucial role of specific solvent-exposed basic residues in supporting this dihydrofolate channeling phenomenon. The electrostatic contribution to the total transfer efficiency is determined via comparison to the transfer efficiency in the non-electrostatic cases (it was estimated to be ∼15% - ∼25%) which is lower than ∼55% in L. major DHFR-TS. This result clearly indicates that the electrostatic channeling in P. falciparum DHFR-TS is modest compared to that in the L. major DHFR-TS enzyme. Whereas L. major DHFR-TS has an abundance of positively charged residues connecting the TS and DHFR active sites, and they are geometrically located on the same face of each monomer (see Fig. 1 A), P. falciparum DHFR-TS (8) has repulsive, negatively charged patches near the electrostatic channeling pathways that are also relatively long and nonlinear in geometry, with the TS and DHFR active sites on each monomer facing opposite planes. This geometry requires the channeled substrate to turn a corner to reach the DHFR active sites (see Fig. 1 B), which leads to increased mixing with bulk solvent and corresponding attenuated reaction rates. Therefore, despite having similar tertiary and quaternary structures, it is clear that subtle differences in structure, active-site geometry, and charge distribution between bifunctional protozoan DHFR-TS Heparin influence both electrostatic-mediated and proximity-mediated substrate channeling. Specifically, the channeling in P. falciparum DHFR-TS is more prominent than that predicted in C. hominis, which has been shown experimentally to not channel dihydrofolate, but was far less efficient than that in L. major DHFR-TS. Thus, our characterization of substrate channeling in this system suggests that suspected P. falciparum DHFR-TS channeling regions would not be an attractive antimalaria drug target, because it appears that the majority of dihydrofolate reaches the DHFR active site via diffusion through bulk solvent rather than through kinetic channeling. In this study, we investigated electrostatic channeling quantitatively using computational models. To simplify the models, we used a spherical representation of dihydrofolate in the Brownian dynamics simulations and a pointlike representation in the Smoluchowski continuum model (5). The errors from this oversimplification are partially corrected by adjusting model parameters such as the effective size of active sites, but future computational studies could benefit from improvements in detailed molecular-scale modeling methodology. One improvement would be to use a flexible, realistic model of dihydrofolate in the Brownian dynamics simulation instead of a simple charged-sphere model of dihydrofolate. Dihydrofolate is a fairly flexible small molecule with a significant dipole moment, and these substrate properties are not considered in this study or previous computational studies of electrostatic substrate channeling. It is likely that dihydrofolate adopts a range of conformations as it traverses the relatively long distance between the TS and DHFR active sites in P. falciparum DHFR-TS. Another potential improvement would be to take into account the nonelectrostatic interactions between dihydrofolate and the enzyme, which may contribute to channeling or interfere with dihydrofolate channeling. Also, the interactions between dihydrofolate and residues on the solvent-exposed surface of the enzyme could induce conformational changes in the enzyme. Such interactions could be considered in the future with more detailed modeling efforts focused on substrate channeling. Features like this could be implemented in future advances in Brownian dynamics simulation software that incorporates flexibility to make improved predictions about the nature of transient protein-dihydrofolate interactions that exist during dihydrofolate channeling in P. falciparum DHFR-TS. In addition, future work on this system could involve lengthy accelerated molecular dynamics simulations (29) of the bifunctional enzyme to search for any interesting dynamics that might influence dihydrofolate channeling or any potential dynamics that might alter the geometry and proximity of the TS and DHFR active sites.