• Journal of Industrial Technology
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• v.20 no.A
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• pp.185-194
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• 2000

In this work we measured the total pressure of the aqueous solutions and the methanol-water solutions dissolved with inorganic salts, at $25^{\circ}C$. In organic electrolytes used in this work were $K_2SO_4$ and $(NH_4)_2SO_4$. Using the measured vapour pressures the activity coefficient of solvents and the mean ionic activity coefficient were obtained through thermodynamic relations. The activity coefficients of solvent and the mean ionic activity coefficirnt obtained in this work were fitted with Macedo's model and Acard's model. Both two models were good agreeable to the vapor pressure and the mean ionic activity coefficient for the electroyte aqueous solutions. For electrolyte /methanol/water solutions, Macedo's model had much deviation from experimental data, while Acard's model showed a good agreement with experimental data.

• Bulletin of the Korean Chemical Society
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• v.15 no.1
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• pp.15-20
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• 1994

The adsorption model in reversed phase liquid chromatography has been critically examined. It has been found that use of the Everett type surface activity coefficient for the solute in the stationary phase is not useful to study the retention characteristics of a nonpolar solute. We suggest a modified model. In this model it is assumed that the displaced modifier molecules from the surface monolayer do not transfer into the bulk mobile phase but stick to the nonpolar solute which has displaced them. In addition, we prefer to use an apparent stationary phase activity coefficient of the soluie instead of the Everett type activity coefficient. This modified adsorption model well explains the mobile and stationary phase effects on the solute retention upon variation of mobile phase composition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1747-1753
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• 2010

In this study, a comparative study was performed to predict the vapor-liquid equilibria with maximum azeotropic pressure for ethanol-benzene binary system between an equation of state model and a liquid activity coefficient model. Peng-Robinson equation of state model with a Panatiotopoulos mixing rules (PRP) was used and NRTL liquid activity coefficient model proposed by Renon was selected. The PRP model, even though it has only two binary adjustable parameters, was not inferior to the NRTL model to predict vapor-liquid equilibria for low pressure region of ethanol-benzene system and showed a better prediction capability for high pressure region of ethanol-benzene system than the NRTL model with three binary interaction parameters.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.203-209
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• 2000

The fluctuation integrals which give useful information in the structure of solution are associated with the mixed direct correlation integral ($C_{12}$) known. Using its weighted arithmetic mean of $C_{11}$ and $C_{22}$ and the activity coefficient model, the fluctuation integrals on solute-solute, solvent-solute, and solvent-solvent can be calculated in the function of mole fraction. In this work, several binary mixtures containing c-hexane were tested and the results on the fluctuation integrals were rather good.

• Korean Chemical Engineering Research
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• v.55 no.5
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• pp.652-659
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• 2017

In the present research, in order to predict activity coefficient of inorganic ions in electrolyte solution of a petroleum system, we studied 13 components in the electrolyte solution, including $H_2O$, $CO_2$ (aq), $H^+$, $Na^+$, $Ba^{2+}$, $Ca^{2+}$, $Sr^{2+}$, $Mg^{2+}$, $SO_4$, $CO_3$, $OH^-$, $Cl^-$, and $HCO_3$. To predict the activity coefficient of the components of the petroleum system (a solid/liquid equilibrium system), activity coefficient model of Extended UNIQUAC was studied, along with its adjustable parameters optimized based on a genetic algorithm. The total calculated error associated with optimizing the adjustable parameters of Extended UNIQUAC model considering the 13 components under study at three temperature levels (298.15, 323.15, and 373.15 K) using the genetic algorithm is found to be 0.07.

• Journal of Integrative Natural Science
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• v.4 no.3
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• pp.210-215
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• 2011

Holographic quantitative structure-activity relationships (HQSAR) is a useful tool to correlates structures with their biological activities. HQSAR is a two dimensional (2D) QSAR methodology, which generates QSAR equations through 2D fingerprint and correlates it with biological activity. Here, we report a 2D-QSAR model for a series of fifty-one 3,4-dihydroxychalcones derivatives utilizing HQSAR methodology. We developed HQSAR model with 6 optimum numbers of components (ONC), which resulted in cross-validated correlation coefficient ($q^2$) of 0.855 with 0.283 standard error of estimate (SEE). The non-cross-validated correlation coefficient (r2) with 0.966 indicates the model is predictive enough for analysis. Developed HQSAR model was binned in to a hologram length of 257. Atomic contribution map revealed the importance of dihydroxy substitution on phenyl ring.

• Bulletin of the Korean Chemical Society
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• v.27 no.10
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• pp.1531-1536
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• 2006

Microsomal prostaglandin $E_2$ synthase (mPGES-1) is an enzyme that is associated with inflammation, pain, fever and cancer. Hologram quantitative structure activity relationship (HQSAR) was conducted on the series of MK-886 compounds acting as mPGES-1 inhibitors. A training set with 24 compounds was used to establish the HQSAR model. The best model was chosen based on the cross-validated correlation coefficient ($q^2$=0.884) and the correlation coefficient($r^2$=0.976). The model was utilized to predict the activity of the eight-test set of compounds giving the predictive $r^2$ value of 0.845. The descriptors of the model are based on fragment distinction (atoms, bond and connectivity) and fragment size (2-5 atoms). The atomic contribution maps generated from HQSAR were useful in identifying the important structural features responsible for the inhibitory activity of MK-886 inhibitors. Based on the generated model, the presence of hydrophobic biphenyl group seems to enhance inhibition of mPGES-1 that is in agreement with the previous experiments. In addition, it seems important for a halogen to be substituted to the biphenyl ring and for an acyl group to be attached to the indole moiety for enhanced activity.

• Journal of Integrative Natural Science
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• v.8 no.3
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• pp.214-220
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• 2015

Cancer has emerged as one of the leading cause of deaths worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of quinazoline-based anticancer agents. Purpose of the study is to understand the structural basis for their inhibitory activity. Comparative molecular field analysis (CoMFA) technique was employed to develop 3D-QSAR model. Ligand-based alignment scheme was used to generate a reliable CoMFA model. The model produced statistically significant results with a cross-validated correlation coefficient ($q^2$) of 0.589 and a non-cross-validated correlation coefficient ($r^2$) of 0.928. Model was further validated by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel and more potent anticancer agents.

• Journal of Integrative Natural Science
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• v.9 no.1
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• pp.1-9
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• 2016

Leucine rich repeat kinase 2 (LRRK2) is a highly promising target for Parkinson's disease (PD) that affects millions of people worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of pyrrolopyrimidine-based selective LRRK2 kinase inhibitors. This study was performed to rationalize the structural requirements responsible for the inhibitory activity of these compounds. A reliable 3D-QSAR model was developed using comparative molecular field analysis (CoMFA) technique. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.539 and a non-cross-validated correlation coefficient ($r^2$) of 0.871. Robustness of the model was further evaluated by bootstrapping and progressive scrambling analysis. This work could assist in designing more potent LRRK2 inhibitors.

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.40-47
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• 2015

Glycogen synthase kinase 3 (GSK-3) is a serine/threonine protein kinase that has recently emerged as a promising target in drug discovery. It is involved in multiple cellular processes and associated with the pathogenesis of several diseases. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of GSK-3 inhibitors to understand the structural basis for inhibitory activity. Comparative molecular field analysis (CoMFA) method was used to derive 3D-QSAR models. A reliable CoMFA model was developed using ligand-based alignment scheme. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.594 and a non-cross-validated correlation coefficient ($r^2$) of 0.943. Robustness of the model was checked by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel compounds with enhanced GSK-3 inhibitory activity.