dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change (ΔrG′o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).

Solubility, Solution Thermodynamics, and Preferential Solvation of Amygdalin in Ethanol + Water Solvent Mixtures

The equilibrium solubility of amygdalin in [ethanol (1) + water (2)] mixtures at 293.15 K to 328.15 K was reported. The thermodynamic properties (standard enthalpy ΔsolnH°, standard entropy ΔsolnS°, and standard Gibbs energy of solution ΔsolnG°) were computed using the generated solubility data via van’t Hoff and Gibbs equations. The dissolution process of amygdalin is endothermic and the driving mechanism in all mixtures is entropy. Maximal solubility was achieved in 0.4 mole fraction of ethanol at 328.15 K and the minimal one in neat ethanol at 293.15 K. Van’t Hoff, Jouyban–Acree–van’t Hoff, and Buchowski–Ksiazczak models were used to simulate the obtained solubility data. The calculated solubilities deviate reasonably from experimental data. Preferential solvation parameters of amygdalin in mixture solvents were analyzed using the inverse Kirkwood–Buff integrals (IKBI) method. Amygdalin is preferentially solvated by water in ethanol-rich mixtures, whereas in water-rich mixtures, there is no clear evidence that determines which of water or ethanol solvents would be most likely to solvate the molecule.

Synthesis of WSi2-W5Si3 Intermetallic Alloy via Self-Propagating High Temperature Synthesis

Intermetallic alloy of tungsten silicide (WSi2-W5Si3) was synthesized by self-propagating high temperature synthesis (SHS) from the reactant of tungsten oxide (WO3) and silicon lump (Si) using magnesium (Mg) as fuel. The standard Gibbs energy minimization method was used to calculate the equilibrium composition of the possible reacting species. The as-SHS products were characterized by X-ray diffraction (XRD) technique. The magnesiothermic reaction process successfully synthesized dense of WSi2-W5Si3intermetallic alloy. According to the experimental results, it can be proposed that the reaction also promotes the phase separation between alloy and oxide slag of the product.

MODELING OF QUASIBINARIES OF Na+, Сa2+ // O2-, F- SYSTEM

Thermodynamic modeling of phase equilibria of the Na +, Ca2 + // O2-, F- system in the frame of the generalized theory of "regular" ionic solutions was carried out. The equations for the activities of the system components were derived. The standard Gibbs energy of the exchange reaction was calculated. The values of the energy parameters of the model were determined and the phase diagrams of the binary systems were constructed.