We describe a computational solvation model called semi-explicit assembly (SEA). SEA water captures much of the physics of explicitsolvent models but with computational speeds approaching those of implicit-solvent models. We use an explicit-water model to precompute properties of water solvation shells around simple spheres, then assemble a solute's solvation shell by combining the shells of these spheres. SEA improves upon implicit-solvent models of solvation free energies by accounting for local solute curvature, accounting for near-neighbor nonadditivities, and treating water's dipole as being asymmetrical with respect to positive or negative solute charges. SEA does not involve parameter fitting, because parameters come from the given underlying explicitsolvation model. SEA is about as accurate as explicit simulations as shown by comparisons against four different homologous alkyl series, a set of 504 varied solutes, solutes taken retrospectively from two solvation-prediction events, and a hypothetical polarsolute series, and SEA is about 100-fold faster than Poisson-Boltzmann calculations.free energy | implicit solvent | transfer W e describe here an approach for computing the free energies of solvation of solutes in water. Aqueous solvation has been modeled at different levels, ranging from detailed quantum mechanics simulations of few-molecule clusters (1, 2), to faster classical simulations using up to tens of thousands of explicit molecules (3-10), to very fast models in which water is treated implicitly as a simple uniform continuous medium (11)(12)(13)(14)(15)(16)(17). For large computations, such as those in typical biomolecule simulations, explicit-water modeling can be slow and expensive, so it is common to use implicit water instead. However, implicit models often require trade-offs in the physics that can limit their accuracies. For example, water is typically treated as a continuum rather than individual particles, and this neglects discrete microscopic effects; nonpolar solvation effects are often assumed to depend only on surface area A (expressed as γA), and not on detailed dispersive interactions and collective consequences of solute shape (18)(19)(20).It would be useful to have a computational model of water that is both fast-approaching the speeds of the fastest implicitsolvent models-and that captures the physics and the transferability of explicit-solvent models. Toward this goal, various improvements of implicit models have been introduced (21, 22), explicit solvents have been coarse-grained (23, 24), and hybrid explicit-implicit models have been developed (25)(26)(27)(28)(29). Here, we take a different approach. We precompute solvation properties of water in explicit-solvent simulations of simple spheres, which we then apply in summations over assemblies about arbitrary solutes. As the details of the solvation response come entirely from the physics of an explicit solvent, this model lacks free parameters from statistical fits to solute molecular transfer free energies, resulting in a ...
We report here a test of the Semi-Explicit Assembly (SEA) model in the solvation free energy category of the SAMPL3 blind prediction event (summer 2011). We tested how dependent the SEA results are on the chosen force field by performing calculations with both the General Amber and OPLS force fields. We compared our SEA results with full molecular dynamics simulations in explicit solvent. Of the 20 submissions, our SEA/OPLS results gave the second smallest RMS errors in free energies compared to experiments. SEA gives results that are very similar to those of its underlying force field and explicit solvent model. Hence, while the SEA water modeling approach is much faster than explicit solvent simulations, its predictions appear to be just as accurate.
Both substances displayed concentration dependent down-regulation of UcP2 expression induced by THs in neonatal rat cardiomyocytes. Because DHSB uncoupled the respiration of isolated rat heart mitochondria while limiting reactive oxygen species (ROS) formation, it may be affecting UcP2 expression in a feedback control fashion. However, SB does neither. Therefore we explored the possibility of both substances limiting TH uptake into cardiomyocytes. TH presence in cardiomyocytes was evaluated by mass-spectrometry and we did not observe any limitation to the uptake of hormones. Because TH actions are primarily mediated by nuclear thyroid receptors and their transcriptional activation, we used reporter plasmid system to assess the SB and DHSB effect on thyroid hormone receptor transcriptional activity in cardiomyocytes. Our data suggest that SB and DHSB modulation of TH-mediated UcP2 expression is not related to their antioxidant ability (DHSB) or lack thereof (SB). Rather both substances influence TH-related processes by affecting the TH-dependent signaling pathway with possible beneficial effects in hyperthyroid patients.
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