Exploring the Influence of Ionic Liquid Anion Structure on Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using Machine Learning.

This article presents an in-depth investigation into the influence of anionic structures of ionic liquids (ILs) on gas-ionic liquid partition coefficients (log K) of organic solutes in three ILs. While the primary objective was to examine whether there is a relationship between the molecular structure of the IL anion component and log K, additionally it was looked at whether the molecular descriptors of the anion in the relationships encode possible molecular interactions during the miscibility and partitioning in the IL. The research involves the compilation of data series of experimental log K values, where the cation component is constant. Such representative data series were obtained for three solutes─benzene, cyclohexane, and methanol─in three ILs with a uniform cationic component of methylimidazoliums. Using multiple linear regression models enhanced with machine learning techniques, the relationship between anionic structures and log K values was successfully quantified and modeled. Systematically selected molecular descriptors describing the anion structure show that in the case of methanol log K is strongly dependent on hydrogen bonds and Coulomb-dipolar interactions with the anion component, while in the case of benzene and cyclohexane the dispersion forces of the anion component are dominant. The outlier analysis and data interpretation highlight the need for extensive experimental data. The results confirm the initial hypothesis and provide valuable information on the role of the structure of the anionic component in determining the partitioning behavior of organic solutes. This knowledge is important for the design and optimization of ILs for specific applications, particularly as solvents in various industrial processes. The research also provides useful information about molecular interactions taking place in the interfaces of IL and organic additives in complex liquid media such as multicomponent electrolyte solutions, for example in energy storage applications.

Comments Regarding "Solubility determination and thermodynamic model analysis of L-α-glyceryl phosphorylcholine in different organic solvents of 278.15-323.15 K".

A polemic is given regarding several of the calculated curve-fit parameters that Zhou and coworkers reported in their published paper. The calculated curve-fit parameters for the Combined Nearly Ideal Binary Solvent/Redlich-Kister, Jouyban-Acree-van't Hoff, Sun and modified Apelblat models were found to give mole fraction solubilities that exceeded unity. Our analysis also found that the mean relative absolute percent deviations provided by the authors were significantly underestimated.

A new set of solute descriptors to calculate solubility of drugs in mono-solvents.

A new set of solute parameters derived from a correlation model using Catalan parameters. The parameters represent the interaction of the solute with the mono-solvents at 298.15K. The computational procedure was adopted from Abraham's solvation model and the obtained results are promising. In this work, the calculated parameters were used to back-calculate the drugs solubility in various mono-solvents at different temperatures employing the van't Hoff's model as the skeleton on the derived model. The obtained mean percentage deviations (MPDs) were in the range of 3.1 to 88.5% with the overall MPD of 29.1%. (1) Derivation of a new set of solute parameters from a correlation model using Catalan parameters; (2) adoption of the calculation method of Abraham's solvation model with the skeleton of van't Hoff's equation; (3) using the achieved parameters for back-calculation of drugs solubility in various mono-solvents; (4) obtaining an overall acceptable mean percentage deviation of 29.1% from calculations.

Preferential Solvation Study of Rosuvastatin in the {PEG400 (1) + Water (2)} Cosolvent Mixture and GastroPlus Software-Based In Vivo Predictions.

Rosuvastatin (RST) is a poorly water-soluble drug responsible for limited in vivo dissolution and subsequently low oral systemic absorption (poor bioavailability). The mole fraction solubility values of RST in various ratios of binary mixtures "{PEG400 (1) + water (2)}" at 298.15 K were employed to investigate the preferential solvation (PS) of RST (3) by the binary components. Moreover, the GastroPlus program predicted the drug dissolution/absorption rates, plasma drug concentration, and compartmental regional drug absorbed from a conventional tablet as compared to the RST-loaded (PEG400 + water) mixture (at x 1 = 0.5) in healthy subjects (considering the fast condition). Fedors' method was adopted to estimate the values of molar volume (314.8 cm3·mol-1) and Hildebrand solubility parameter (28.08 MPa1/2) of RST. The results of inverse Kirkwood-Buff integrals showed the PS of RST by PEG400 as observed in all studied ratios of the binary mixture. The highest PS value (δx 1,3 = 1.65 × 10-2) for RST by PEG400 was attained at x 1 = 0.5. Finally, the GastroPlus program predicted the maximum dissolution rate [20 mg within 15 min as compared to pure RST (1.5 mg within 15 min)]. Moreover, the program predicted increased in vivo oral absorption (1.2 µg/mL) and enhanced regional absorption (95.3%) of RST from upper segments of the gastrointestinal tract for the RST-loaded PEG400 + water mixture in humans as compared to conventional tablets (87.5% as total regional absorption and 0.88 µg/mL as in vivo absorption). Hence, the present binary system ferrying RST can be a promising strategy to control systemic dyslipidemia after oral or subcutaneous administration.

Effect of N-Methyl-pyrrolidone (NMP) on the Equilibrium Solubility of Meloxicam in Aqueous Media: Correlation, Dissolution Thermodynamics, and Preferential Solvation.

Meloxicam is an analgesic and anti-inflammatory drug widely prescribed in current therapeutics that exhibits very low solubility in water. Thus, this physicochemical property has been studied in N-methyl-pyrrolidone (NMP)-aqueous mixtures at several temperatures to expand the solubility database about pharmaceutical compounds in aqueous-mixed solvents. The flask-shake method and UV-vis spectrophotometry were used for meloxicam solubility determination as a function of temperature and mixture composition. Several cosolvency models, including the Jouyban-Acree model, were challenged for equilibrium solubility correlation and/or prediction. The van't Hoff and Gibbs equations were employed here to calculate the apparent standard thermodynamic quantities for the dissolution and mixing processes of this drug in these aqueous mixtures. Inverse Kirkwood-Buff integrals were employed to calculate the preferential solvation parameters of meloxicam by NMP in all mixtures. Meloxicam equilibrium solubility increased with increasing temperature, and maximal solubilities were observed in neat NMP at all temperatures. The mole fraction solubility of meloxicam increased from 1.137 × 10-6 in neat water to 3.639 × 10-3 in neat NMP at 298.15 K. The Jouyban-Acree model correlated the meloxicam solubility in these mixtures very well. Dissolution processes were endothermic and entropy-driven in all cases, except in neat water, where nonenthalpy- nor entropy-driven was observed. Apparent Gibbs energies of dissolution varied from 34.35 kJ·mol-1 in pure water to 7.99 kJ·mol-1 in pure NMP at a mean harmonic temperature of 303.0 K. A nonlinear enthalpy-entropy relationship was observed in the plot of dissolution enthalpy vs dissolution Gibbs energy. Meloxicam is preferentially hydrated in water-rich mixtures but preferentially solvated by NMP in the composition interval of 0.16 < x 1 < 1.00.

Machine Learning Quantitative Structure-Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons.

Ionic liquids (ILs) are known for their unique characteristics as solvents and electrolytes. Therefore, new ILs are being developed and adapted as innovative chemical environments for different applications in which their properties need to be understood on a molecular level. Computational data-driven methods provide means for understanding of properties at molecular level, and quantitative structure-property relationships (QSPRs) provide the framework for this. This framework is commonly used to study the properties of molecules in ILs as an environment. The opposite situation where the property is considered as a function of the ionic liquid does not exist. The aim of the present study was to supplement this perspective with new knowledge and to develop QSPRs that would allow the understanding of molecular interactions in ionic liquids based on the structure of the cationic moiety. A wide range of applications in electrochemistry, separation and extraction chemistry depends on the partitioning of solutes between the ionic liquid and the surrounding environment that is characterized by the gas-ionic liquid partition coefficient. To model this property as a function of the structure of a cationic counterpart, a series of ionic liquids was selected with a common bis-(trifluoromethylsulfonyl)-imide anion, [Tf2N]-, for benzene, hexane and cyclohexane. MLR, SVR and GPR machine learning approaches were used to derive data-driven models and their performance was compared. The cross-validation coefficients of determination in the range 0.71-0.93 along with other performance statistics indicated a strong accuracy of models for all data series and machine learning methods. The analysis and interpretation of descriptors revealed that generally higher lipophilicity and dispersion interaction capability, and lower polarity in the cations induces a higher partition coefficient for benzene, hexane, cyclohexane and hydrocarbons in general. The applicability domain analysis of models concluded that there were no highly influential outliers and the models are applicable to a wide selection of cation families with variable size, polarity and aliphatic or aromatic nature.

Drug Solubility Correlation Using the Jouyban-Acree Model: Effects of Concentration Units and Error Criteria.

An important factor affecting the model accuracy is the unit expression type for solute and solvent concentrations. One can report the solute and solvent concentration in various units and compare them with various error scales. In order to investigate the unit and error scale expression effects on the accuracy of the Jouyban-Acree model, in the current study, seventy-nine solubility data sets were collected randomly from the published articles and solute and solvent concentrations in the investigated systems were expressed in various units. Mass fraction, mole fraction, and volume fraction were the employed concentration units for the solvent compositions, and mole fraction, molar, and gram/liter were the investigated concentration units for the solutes. The solubility data, with various solute/solvent concentration units, were correlated using the Jouyban-Acree model, and the accuracy of each model for correlating the data was investigated by calculating different error scales and discussed.

Descriptors for some compounds with pharmacological activity; calculation of properties.

Abraham model solute descriptors have been determined for nisoldipine, nizatidine, loratadine, zonisamide, oxaprozin, rebamipide, domperidone, temozolomide, 'florfenicol', florfenicol A, dapsone, chrysin, benorilate, ß-lapachone, and Ipriflavone based on published partition coefficients, molar solubilities and gas chromatographic retention indices. The calculated solute descriptors, combined with our previously published Abraham model correlations, are used to predict several important physicochemical and biological properties, such as air-water, air-blood, air-lung, air-fat, air-skin, water-lipid, water-membrane and water-skin partition coefficients, as well as permeation from water through skin.

Preferential Solvation Study of the Synthesized Aldose Reductase Inhibitor (SE415) in the {PEG 400 (1) + Water (2)} Cosolvent Mixture and GastroPlus-Based Prediction.

(Z)-N-Benzyl-2-{2,4-dioxo-5-(4-prop-2-yl-1-yloxyl)benzylidene)thiazolin-3-yl)}acetamide (SE415) is a novel aldose reductase inhibitor used in the management of diabetes mellitus (DM) and associated complications. Herein, the drug was solubilized (mole fraction solubility) in a "PEG 400 (polyethylene glycol 400) + water" mixture of various ratios at 298.15 K. We reported the preferential solvation of SE415 by PEG 400 using Kirkwood-Buff integrals, the thermodynamic functional parameter, in vitro dissolution, and GastroPlus-based predictions for in vivo performance. The result of Hansen solubility parameter analysis suggested PEG 400 as a suitable solvent for SE415 solubilization at 298.0 K, followed by prediction of several physicochemical properties. In the preferential solvation study, the molar volume, Hildebrand solubility parameters, and the molecular radius of SE415 were estimated as 258.4 cm3·mol-1, 27.62 MPa1/2, and 0.468 nm, respectively, using Fedors' method. The inverse Kirkwood-Buff integrals indicated that the preferential solvation of SE415 by PEG 400 occurred in all studied ratios of the (PEG 400 + water) mixtures. The maximum value (δx 1,3 = 1.21 × 10-2) of the preferential solvation of SE415 by PEG 400 was achieved at x 1 = 0.15. Then, using GastroPlus software, the maximum dissolution, improved in vivo oral absorption, and high regional compartmental absorption (total 99.0%) of SE415 in humans were predicted. Finally, the solubility data were correlated/predicted using various cosolvency models with satisfactory results. Thus, the binary cosolvent system can be a promising approach for enhanced oral absorption in controlling DM and associated complications in humans.

Revision and Extension of a Generally Applicable Group-Additivity Method for the Calculation of the Standard Heat of Combustion and Formation of Organic Molecules.

The calculation of the heats of combustion ΔH°c and formation ΔH°f of organic molecules at standard conditions is presented using a commonly applicable computer algorithm based on the group-additivity method. This work is a continuation and extension of an earlier publication. The method rests on the complete breakdown of the molecules into their constituting atoms, these being further characterized by their immediate neighbor atoms. The group contributions are calculated by means of a fast Gauss-Seidel fitting calculus using the experimental data of 5030 molecules from literature. The applicability of this method has been tested by a subsequent ten-fold cross-validation procedure, which confirmed the extraordinary accuracy of the prediction of ΔH°c with a correlation coefficient R2 and a cross-validated correlation coefficient Q2 of 1, a standard deviation σ of 18.12 kJ/mol, a cross-validated standard deviation S of 19.16 kJ/mol, and a mean absolute deviation of 0.4%. The heat of formation ΔH°f has been calculated from ΔH°c using the standard enthalpies of combustion for the elements, yielding a correlation coefficient R2 for ΔH°f of 0.9979 and a corresponding standard deviation σ of 18.14 kJ/mol.

Evaluation of nine condensed-phase force fields of the GROMOS, CHARMM, OPLS, AMBER, and OpenFF families against experimental cross-solvation free energies.

Experimental solvation free energies are nowadays commonly included as target properties in the validation of condensed-phase force fields, sometimes even in their calibration. In a previous article [Kashefolgheta et al., J. Chem. Theory. Comput., 2020, 16, 7556-7580], we showed how the involved comparison between experimental and simulation results could be made more systematic by considering a full matrix of cross-solvation free energies . For a set of N molecules that are all in the liquid state under ambient conditions, such a matrix encompasses N×N entries for considering each of the N molecules either as solute (A) or as solvent (B). In the quoted study, a cross-solvation matrix of 25 × 25 experimental value was introduced, considering 25 small molecules representative for alkanes, chloroalkanes, ethers, ketones, esters, alcohols, amines, and amides. This experimental data was used to compare the relative accuracies of four popular condensed-phase force fields, namely GROMOS-2016H66, OPLS-AA, AMBER-GAFF, and CHARMM-CGenFF. In the present work, the comparison is extended to five additional force fields, namely GROMOS-54A7, GROMOS-ATB, OPLS-LBCC, AMBER-GAFF2, and OpenFF. Considering these nine force fields, the correlation coefficients between experimental values and simulation results range from 0.76 to 0.88, the root-mean-square errors (RMSEs) from 2.9 to 4.8 kJ mol-1, and average errors (AVEEs) from -1.5 to +1.0 kJ mol-1. In terms of RMSEs, GROMOS-2016H66 and OPLS-AA present the best accuracy (2.9 kJ mol-1), followed by OPLS-LBCC, AMBER-GAFF2, AMBER-GAFF, and OpenFF (3.3 to 3.6 kJ mol-1), and then by GROMOS-54A7, CHARM-CGenFF, and GROMOS-ATB (4.0 to 4.8 kJ mol-1). These differences are statistically significant but not very pronounced, and are distributed rather heterogeneously over the set of compounds within the different force fields.

Calculation of the Vapour Pressure of Organic Molecules by Means of a Group-Additivity Method and Their Resultant Gibbs Free Energy and Entropy of Vaporization at 298.15 K.

The calculation of the vapour pressure of organic molecules at 298.15 K is presented using a commonly applicable computer algorithm based on the group-additivity method. The basic principle of this method rests on the complete breakdown of the molecules into their constituting atoms, further characterized by their immediate neighbour atoms. The group contributions are calculated by means of a fast Gauss-Seidel fitting algorithm using the experimental data of 2036 molecules from literature. A ten-fold cross-validation procedure has been carried out to test the applicability of this method, which confirmed excellent quality for the prediction of the vapour pressure, expressed in log(pa), with a cross-validated correlation coefficient Q2 of 0.9938 and a standard deviation σ of 0.26. Based on these data, the molecules' standard Gibbs free energy ΔG°vap has been calculated. Furthermore, using their enthalpies of vaporization, predicted by an analogous group-additivity approach published earlier, the standard entropy of vaporization ΔS°vap has been determined and compared with experimental data of 1129 molecules, exhibiting excellent conformance with a correlation coefficient R2 of 0.9598, a standard error σ of 8.14 J/mol/K and a medium absolute deviation of 4.68%.

Reference Materials for Phase Equilibrium Studies. 1. Liquid-Liquid Equilibria (IUPAC Technical Report).

This article is the first of three projected IUPAC Technical Reports resulting from IUPAC Project 2011-037-2-100 (Reference Materials for Phase Equilibrium Studies). The goal of that project was to select reference systems with critically evaluated property values for the validation of instruments and techniques used in phase equilibrium studies for mixtures. This Report proposes seven systems for liquid-liquid equilibrium studies, covering the four most common categories of binary mixtures: aqueous systems of moderate solubility, non-aqueous systems, systems with low solubility, and systems with ionic liquids. For each system, the available literature sources, accepted data, smoothing equations, and estimated uncertainties are given.

Evaluating Classical Force Fields against Experimental Cross-Solvation Free Energies.

Experimental solvation free energies are nowadays commonly included as target properties in the validation and sometimes even in the calibration of condensed-phase force fields. However, this is often done in a nonsystematic fashion, by considering available solvation free energies involving an arbitrary collection of solutes in a limited set of solvents (e.g., water, octanol, chloroform, cyclohexane, or hexane). Here, this approach is made more systematic by introducing the concept of cross-solvation free energies ΔsGA:B⊖ for a set of N molecules that are all in the liquid state under ambient conditions, namely the matrix of N2 entries for ΔsGA:B⊖ considering each of the N molecules either as a solute (A) or as a solvent (B). Relying on available experimental literature followed by careful data curation, a complete ΔsGA:B⊖ matrix of 625 entries is constructed for 25 molecules with one to seven carbon atoms representative for alkanes, chloroalkanes, ethers, ketones, esters, alcohols, amines, and amides. This matrix is then used to compare the relative accuracies of four popular condensed-phase force fields: GROMOS-2016H66, OPLS-AA, AMBER-GAFF, and CHARMM-CGenFF. In broad terms, and in spite of very different force-field functional-form choices and parametrization strategies, the four force fields are found to perform similarly well. Relative to the experimental values, the root-mean-square errors range between 2.9 and 4.0 kJ·mol-1 (lowest value of 2.9 for GROMOS and OPLS), and the average errors range between -0.8 and +1.0 kJ·mol-1 (lowest magnitude of 0.2 for AMBER and CHARMM). These differences are statistically significant but not very pronounced, especially considering the influence of outliers, some of which possibly caused by inaccurate experimental data.

Critical Comments on "Assessment of the Thermodynamic Properties of DL-p-Mentha-1,8-diene, 4-Isopropyl-1-Methylcyclohexene (DL-Limonene) by Inverse Gas Chromatography (IGC)".

A polemic is given regarding the calculated thermodynamic quantities reported in the published paper by Farschi and coworkers. The graph used to calculate the molar heat of sorption of organic probe molecules onto the liquid DL-limonene stationary phase erroneously plots the reciprocal of the centigrade temperatures, rather than the reciprocal of the Kelvin temperatures. Molar heats of vaporization of the organic probe molecules reported in the paper are abnormally small and are not in accord with published values determined from calorimetric and vapor pressure measurements.

Comments on "Classification of biphasic solvent systems according to Abraham descriptors for countercurrent chromatography".

Abraham model correlations reported by Marlot and coworkers for the 1-octanol/water, 1-butanol/water, ethyl acetate/water, and heptane/methanol biphasic partitioning systems are compared to previously published Abraham model correlations. The previously published correlations for the fore-mentioned partitioning systems are based on more experimental data points, and exhibit much better descriptive ability as evidenced by much smaller standard deviations/standard errors and larger squared correlation coefficients.

PMFF: Development of a Physics-Based Molecular Force Field for Protein Simulation and Ligand Docking.

The physics-based molecular force field (PMFF) was developed by integrating a set of potential energy functions in which each term in an intermolecular potential energy function is derived based on experimental values, such as the dipole moments, lattice energy, proton transfer energy, and X-ray crystal structures. The term "physics-based" is used to emphasize the idea that the experimental observables that are considered to be the most relevant to each term are used for the parameterization rather than parameterizing all observables together against the target value. PMFF uses MM3 intramolecular potential energy terms to describe intramolecular interactions and includes an implicit solvation model specifically developed for the PMFF. We evaluated the PMFF in three ways. We concluded that the PMFF provides reliable information based on the structure in a biological system and interprets the biological phenomena accurately by providing more accurate evidence of the biological phenomena.

Descriptors for terpene esters from chromatographic and partition measurements: Estimation of human odor detection thresholds.

We have used gas chromatographic retention data together with other data to obtain Abraham descriptors for 30 terpene esters. These include the air-water partition coefficient, as log Kw, for which no experimental values are available for any terpene ester. The other descriptors are the ester dipolarity, S, the hydrogen bond basicity, B, (the ester hydrogen bond acidity is zero for the esters studied), and L the logarithm of the air-hexadecane partition coefficient. Both S and B are larger than those for simple aliphatic esters, as expected from the terpene ester structures that include ring systems and ethylenic double bonds. These descriptors can then be used to obtain a large number of physicochemical and environmental properties of terpene esters. We have analyzed experimental results on human odor detection thresholds and have constructed another equation for the calculation of these thresholds, to go with a previous equation that we have reported. Then the descriptors for terpene esters can be used to estimate the important odor detection thresholds.

Solvation Descriptors for Zwitterionic α-Aminoacids; Estimation of Water-Solvent Partition Coefficients, Solubilities, and Hydrogen-Bond Acidity and Hydrogen-Bond Basicity.

The literature data on solubilities and water-solvent partition coefficients have been used to obtain properties or "Absolv descriptors" for zwitterionic α-aminoacids: glycine, α-alanine (α-aminopropanoic acid), α-aminobutanoic acid, norvaline (α-aminopentanoic acid), norleucine (α-aminohexanoic acid), valine (α-amino-3-methylbutanoic acid), leucine (α-amino-4-methylpentanoic acid), and α-phenylalanine. Together with equations that we have previously constructed, these descriptors can be used to estimate further solubilities and partition coefficients in a variety of organic solvents and in water-methanol and water-ethanol mixtures. It is shown that equations for neutral solutes are inadequate for the description of solubilities and partition coefficients for these α-aminoacids, and our equations developed for use with both neutral and ionic solutes must be used. The Absolv descriptors include those for hydrogen-bond acidity, A, and hydrogen-bond basicity, B. We find that both of these descriptors are far smaller in value than those for compounds that contain the corresponding ionic groups. Thus, A for α-alanine is 0.28, but A for the ethylammonium cation is 1.31; B for α-alanine is 0.83, and yet B for the acetate anion is no less than 2.93. The additional descriptors that we developed for equations that involve ions, J + and J -, are very significant for the α-aminoacids, although numerically smaller than for ionic species such as EtNH3 + and CH3CO2 -.

Generalized molecular solvation in non-aqueous solutions by a single parameter implicit solvation scheme.

In computer simulations of solvation effects on chemical reactions, continuum modeling techniques regain popularity as a way to efficiently circumvent an otherwise costly sampling of solvent degrees of freedom. As effective techniques, such implicit solvation models always depend on a number of parameters that need to be determined earlier. In the past, the focus lay mostly on an accurate parametrization of water models. Yet, non-aqueous solvents have recently attracted increasing attention, in particular, for the design of battery materials. To this end, we present a systematic parametrization protocol for the Self-Consistent Continuum Solvation (SCCS) model resulting in optimized parameters for 67 non-aqueous solvents. Our parametrization is based on a collection of ≈6000 experimentally measured partition coefficients, which we collected in the Solv@TUM database presented here. The accuracy of our optimized SCCS model is comparable to the well-known universal continuum solvation model (SMx) family of methods, while relying on only a single fit parameter and thereby largely reducing statistical noise. Furthermore, slightly modifying the non-electrostatic terms of the model, we present the SCCS-P solvation model as a more accurate alternative, in particular, for aromatic solutes. Finally, we show that SCCS parameters can, to a good degree of accuracy, also be predicted for solvents outside the database using merely the dielectric bulk permittivity of the solvent of choice.