Prediction of aqueous solubilities of solid carboxylic acids with COSMO-RS

The methodology for the prediction of aqueous solubilities of solid organic compounds, and their temperature dependence, based on the Conductor-like Screening Model for Real Solvents (COSMO-RS/COSMOtherm) procedure, is presented and evaluated. The predictive capability of the quantum chemistry based program and the applied methodology was tested on the most common solid carboxylic acids. From the temperature dependence of the solubilities, the mean apparent enthalpies of solution were derived. The results obtained for a set of 27 carboxylic acids, consisting of aromatic carboxylic acids, dicarboxylic acids, as well as hydroxycarboxylic acids, are in good agreement with the experimental solubility data and their dependence with the temperature. The mean apparent enthalpies of solution, although of the same order of magnitude of the experimentally values, seem to be systematically underestimated.     

Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS

Performance of COSMO-RS method as a tool for partition and distribution modeling in 20 solvent pairs—composed of neutral or acidic aqueous solution and organic solvents of different polarity, ranging from alcohols to toluene and hexane—was evaluated. Experimental partition/distribution data of lignin-related and drug-like compounds (neutral, acidic, moderately basic) were used as reference. Several aspects of partition modeling were addressed: accounting for mutual saturation of aqueous and organic phases, variability of systematic prediction errors across solvent pairs, taking solute ionization into account. COSMO-RS was found to predict extraction outcome for both ligneous and drug-like compounds in various solvent pairs fairly well without any additional empirical input. The solvent-specific systematic errors were found to be moderate, despite being statistically significant, and related to the solvent hydrophobicity. Accounting for mutual solubilities of the two liquids was proven crucial in cases where water was considerably soluble in the organic solvent. The root mean square error of a priori logP prediction varied, depending mainly on the solvent pair, from 0.2 to 0.7, overall value being 0.6 log units. The accuracy was higher in case of hydrophilic than hydrophobic solvents. The logD predictions were less accurate, due to pK_a prediction being an additional source of error, and also because of the complexity of modeling the behaviour of ionic species in the two-phase system. A simple correction for partitioning of free ions was found to notably improve logD prediction accuracy in case of the most hydrophilic organic phase (butanol/water).     

Prediction of the Solubilities of Water in Hydrocarbons with COSMO-RS and Interpretation of the Solubility Characteristics

The solubilities of water in various hydrocarbons are usually needed to assess the water content in oil products. Because the solubilities of water in hydrocarbons are very small, which usually leads to large deviations in experiments, and because we have trouble carrying out experiments on bulk hydrocarbons, it is necessary to develop a more convenient molecular simulation approach to predict the solubility. In this paper, COSMO-RS, a statistical thermodynamic method based on quantum chemistry, has been employed to obtain the solubilities of water in n-alkanes, alkylcyclohexanes, alkylbenzenes and 1-alkenes by calculating the difference of the thermodynamic properties during the dissolution process. The predictions of COSMO-RS were compared with the experimental data, as well as those of API correlations and the Tsonopoulos correlation. The results indicate that COSMO-RS can better predict the trends of the solubility with high accuracy, where the deviations are within ± 29.41%. The characteristics of the solubilities of water in various hydrocarbons are interpreted systemically, especially for the influence of carbon number, CN. It particularly focuses on the non-monotonicity of the solubility curves of water in n-alkanes with the increase of CN. In addition, the effect of temperature on the characteristic of solubility is simultaneously investigated.     

COSMOfrag: a novel tool for high-throughput ADME property prediction and similarity screening based on quantum chemistry

The COSMO-RS (Continuum Solvation Model for Real Solvents) method has proven its broad applicability for the accurate prediction of thermodynamic, environmental, or physiological properties. On the basis of quantum chemical calculations with COSMO, COSMO-RS calculations were unavoidably restricted to small- to medium-sized compound sets, because of the time demand of the COSMO calculations. The COSMOfrag method, presented here, overcomes this restriction by replacing the costly quantum chemistry step with a selection of suitable fragments from a database of, presently, 40,000 DFT/COSMO precalculated molecules. Since, in the COSMO-RS picture, any molecular information is gathered in the so-called sigma profiles, COSMOfrag replaces the single sigma profile with a composition of partial sigma profiles, selected by the use of extensive similarity searching algorithms. On five representative datasets, the accuracy loss of COSMOfrag versus full COSMO-RS calculations has been shown to be only in the range of 0.05 log units. From the performance point of view, it is now possible to carry out COSMO-RS property calculations for more than 100,000 compounds a day per standard PC CPU.     

Estimation of aqueous solubility for a diverse set of organic compounds based on molecular topology

An accurate and generally applicable method for estimating aqueous solubilities for a diverse set of 1297 organic compounds based on multilinear regression and artificial neural network modeling was developed. Molecular connectivity, shape, and atom-type electrotopological state (E-state) indices were used as structural parameters. The data set was divided into a training set of 884 compounds and a randomly chosen test set of 413 compounds. The structural parameters in a 30-12-1 artificial neural network included 24 atom-type E-state indices and six other topological indices, and for the test set, a predictive r2 = 0.92 and s = 0.60 were achieved. With the same parameters the statistics in the multilinear regression were r2 = 0.88 and s = 0.71, respectively.     

Development of an automatic estimation system for both the partition coefficient and aqueous solubility

Summary A computer program has been developed for estimating both the partition coefficient between 1-octanol and water phases and the aqueous solubility from the structural formula. This system is an extended version of a previously described program entitled CHEMICALC for the automatic estimation of the partition coefficient. The aqueous solubility is estimated via two pathways. The first is based on the linear relationship between logarithms of the aqueous solubilities of 497 compounds and their estimated 1-octanol/water partition coefficients. In the second, combined handling of two available group contribution methods of Irmann [Chem. Ing. Tech., 37 (1965) 789] and Wakita et al. [Chem. Pharm. Bull., 34 (1986) 4663] is adopted according to compound type. Some revisions and extensions of the methods for estimating the aqueous solubility have been made in both pathways, and the accuracy of the estimated aqueous solubilities for 497 compounds is discussed.     

Blind prediction test of free energies of hydration with COSMO-RS

The COSMO-RS method, a combination of the quantum chemical dielectric continuum solvation model COSMO with COSMO-RS, a statistical thermodynamics treatment of surface interactions, simulations, has been used for the direct, blind prediction of free energies of hydration within the SAMPL challenge. Straight application of the latest version of the COSMOtherm implementation in combination with a rigorous conformational sampling yielded a predictive accuracy of 1.56 kcal/mol (RMSE) for the 23 compounds of the blind prediction dataset. Due to the uncertainties of the extrapolations and assumptions involved in the derivation of the experimental data, the accuracy of the predicted data may be considered to be within the noise level of the experimental data.     

Some conclusions regarding the predictions of tautomeric equilibria in solution based on the SAMPL2 challenge

The COSMO-RS method, a combination of the quantum chemical dielectric continuum solvation model COSMO with a COSMO based statistical thermodynamics of surface interactions, has been used in its COSMOtherm implementation for the direct, blind prediction of tautomeric equilibria within the SAMPL2 challenge. Since the quantum chemical level underlying COSMOtherm, i.e. BP/TZVP DFT-calculations, is known to be of limited accuracy with respect to reaction energies, we tested MP2 reaction energy corrections in addition. As expected, the straight application of the latest version of COSMOtherm yielded a poor predictive accuracy of ~4 kcal/mol (RMSE) for the eight compounds of the blind prediction data set, and the MP2-corrected predictions reduced the average error considerably to ~1.2 kcal/mol. But a more detailed analysis shows that this improvement is not systematic and mostly a lucky coincidence on the small data set. The systematic results of COSMOtherm allow for an efficient empirical correction with an RMSE of 0.61 kcal/mol. This allows for systematic predictions for the most important case of generalized keto-enol tautomerism.     

Prediction of solubility of drugs by conductor-like screening model for real solvents

The solubility of drugs in solvents is fundamentally important for drug development and manufacturing. As the experimental measurements of the solubility are extremely laborious tasks, reliable prediction methods are highly required. We have employed the conductor-like screening model for real solvents (COSMO-RS) in predicting the solubility of drugs and drug-like compounds in various solvent systems. We also evaluated the salt effect on the solubility of caffeine using this method. The present results demonstrated that COSMO-RS has reasonably reproduced the experimental data and have proved that this method is generally available in predicting the solubility of drugs.     

Liquid Phase Behavior in Systems of 1-Butyl-3-alkylimidazolium bis{(trifluoromethyl)sulfonyl}imide Ionic Liquids with Water: Influence of the Structure of the C5 Alkyl Substituent

In the present paper a study of the liquid phase behavior in aqueous systems of imidazolium-based ionic liquids (ILs) with the bis{(trifluoromethyl)sulfonyl}imide anion is addressed. To highlight the influence of the C5 alkyl side group structure on their properties, a series of ILs with linear, branched, and cyclic substituents was studied. As was already shown in our previous work, very subtle changes in the cation structure at the molecular scale can have a significant and unexpected impact on the bulk properties. Therefore, in this work, the mutual solubilities of 1-butyl-3-alkylimidazolium bis{(trifluoromethyl)sulfonyl}imide ionic liquids and water were studied, both experimentally and by modeling, at atmospheric pressure as a function of temperature from 293.15 to 328.15 K. The solubilities of the ionic liquids in water are very low, typically around 10^?5 mole fraction units and were measured by a direct analytical method, making use of UV–Vis spectrophotometry. The solubilities of water in the ionic liquids were found to be around 0.20 mole fraction units and were measured using the cloud-point method. In addition to the experimental data, the liquid–liquid equilibria in the systems were modeled using the COSMO-RS methodology. Phase diagrams and the critical solution points were also estimated by applying the universal scaling laws based on the 3D Ising model, taking into account the non-linearity of the diameter and crossover to mean-field behavior.