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Solubility parameter based methods have long been a valuable tool for solvent formulation and selection. Of these methods, the MOdified Separation of Cohesive Energy Density (MOSCED) has recently been shown to correlate well the equilibrium solubility of multifunctional non-electrolyte solids. However, before it can be applied to a novel solute, a limited amount of reference solubility data is required to regress the necessary MOSCED parameters. Here we demonstrate for the solutes methylparaben, ethylparaben, propylparaben, butylparaben, lidocaine and ephedrine how conventional molecular simulation free energy calculations or electronic structure calculations in a continuum solvent, here the SMD or SM8 solvation model, can instead be used to generate the necessary reference data, resulting in a predictive flavor of MOSCED. Adopting the melting point temperature and enthalpy of fusion of these compounds from experiment, we are able to predict equilibrium solubilities. We find the method is able to well correlate the (mole fraction) equilibrium solubility in non-aqueous solvents over four orders of magnitude with good quantitative agreement.

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of [Formula: see text] log units (ranking 15 out of 62 entries), the correlation coefficient (R) was [Formula: see text] (ranking 35), and [Formula: see text] of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

There is a pressing need for new therapeutics to reactivate covalently inactivated acetylcholinesterase (AChE) due to exposure to organophosphorus (OP) compounds. Current reactivation therapeutics (RTs) are not broad-spectrum and suffer from other liabilities, specifically the inability to cross the blood-brain-barrier. Additionally, the chemical diversity of available therapeutics is small, limiting opportunities for structure-activity relationship (SAR) studies to aid in the design of more effective compounds. In order to find new starting points for the development of oxime-containing therapeutic reactivators and to increase our base of knowledge, we have employed a combination of computational and experimental procedures to identify additional compounds with the real or potential ability to reactivate AChE while augmenting and complementing current knowledge. Computational methods were used to identify previously uninvestigated oxime-containing molecules. Experimentally, six compounds were found with reactivation capabilities comparable to, or exceeding, those of 2-pralidoxime (2-PAM) against a panel of AChE inactivated by paraoxon, diisopropylfluorophosphate (DFP), fenamiphos, and methamidophos. One compound showed enhanced reactivation ability against DFP and fenamiphos, the least tractable of these OPs to be reactivated.

Currently little is known about the biomechanical environment in decellularized tissue. The goal of this research is to quantify the mechanical microenvironment in decellularized liver, for varying organ-scale perfusion conditions, using a combined experimental/computational approach. Needle-guided ultra-miniature pressure sensors were inserted into liver tissue to measure parenchymal fluid pressure ex-situ in portal vein-perfused native (n=5) and decellularized (n=7) ferret liver, for flow rates from 3-12mL/min. Pressures were also recorded at the inlet near the portal vein cannula to estimate total vascular resistance of the specimens. Experimental results were fit to a multiscale computational model to simulate perfusion conditions inside native versus decellularized livers for four experimental flow rates. The multiscale model consists of two parts: an organ-scale electrical analog model of liver hemodynamics and a tissue-scale model that predicts pore fluid pressure, pore fluid velocity, and solid matrix stress and deformation throughout the 3D hepatic lobule. Distinct models were created for native versus decellularized liver. Results show that vascular resistance decreases by 82% as a result of decellularization. The hydraulic conductivity of the decellularized liver lobule, a measure of tissue permeability, was 5.6 times that of native liver. For the four flow rates studied, mean fluid pressures in the decellularized lobule were 0.6-2.4mmHg, mean fluid velocities were 211-767μm/s, and average solid matrix principal strains were 1.7-6.1%. In the future this modeling platform can be used to guide the optimization of perfusion seeding and conditioning strategies for decellularized scaffolds in liver bioengineering., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

A generalized lattice-spring lattice-Boltzmann model (GLLM) is introduced by adding a three-body force in the traditional lattice-spring model. This method is able to deal with bending deformation of flexible biological bodies in fluids. The interactions between elastic solids and fluid are treated with the immersed boundary-lattice Boltzmann method. GLLM is validated by comparing the present results with the existing theoretical and simulation results. As an application of GLLM, swimming of flagellum in fluid is simulated and propulsive force as a function of driven frequency and fluid structures at various Reynolds numbers 0.15-5.1 are presented in this paper., (Copyright © 2014 Elsevier Ltd. All rights reserved.)