Screening of ionic liquids for efficient extraction of methylxanthines using COSMO-RS methodology

Computer-Aided Molecular Design of Ionic Liquids as Advanced Process Media: A Review from Fundamentals to Applications

The unique physicochemical properties, flexible structural tunability, and giant chemical space of ionic liquids (ILs) provide them a great opportunity to match different target properties to work as advanced process media. The crux of the matter is how to efficiently and reliably tailor suitable ILs toward a specific application. In this regard, the computer-aided molecular design (CAMD) approach has been widely adapted to cover this family of high-profile chemicals, that is, to perform computer-aided IL design (CAILD). This review discusses the past developments that have contributed to the state-of-the-art of CAILD and provides a perspective about how future works could pursue the acceleration of the practical application of ILs. In a broad context of CAILD, key aspects related to the forward structure-property modeling and reverse molecular design of ILs are overviewed. For the former forward task, diverse IL molecular representations, modeling algorithms, as well as representative models on physical properties, thermodynamic properties, among others of ILs are introduced. For the latter reverse task, representative works formulating different molecular design scenarios are summarized. Beyond the substantial progress made, some future perspectives to move CAILD a step forward are finally provided.

Overview and thermodynamic modelling of deep eutectic solvents as co-solvents to enhance drug solubilities in water

The poor water solubility of active pharmaceutical ingredients (APIs) is a major challenge in the pharmaceutical industry. Co-solvents are sometimes added to enhance drug dissolution. A novel group of co-solvents, the Deep Eutectic Solvents (DES), have gained interest in the pharmaceutical field due to their good solvent power, biodegradability, sustainability, non-toxicity, and low cost. In this study, we first provide an overview of all the literature solubility studies involving a drug or API + water + DES, which can be a valuable list to some researchers. Then, we analyze these systems with focus on each individual drug/API and provide statistical information on each. A similar analysis is carried out with focus on the individual DESs. An investigation of the numeric values of the water-solubility enhancement by the different DESs for various drugs indicates that DESs are indeed effective co-solvents, with varying degrees of solubility enhancement, even up to 15-fold. This is strongly encouraging, indicating the need for further studies to find the most promising DESs for solubility enhancement. However, time-consuming and costly trial and error should be prevented by first screening, using theoretical-based or thermodynamic-based models. Based on this conclusion, the second part of the study is concerned with investigating and suggesting accurate thermodynamic approaches to tackle the phase equilibrium modeling of such systems. For this purpose, a large data bank was collected, consisting of 2009 solubility data of 25 different drugs/APIs mixed with water and 31 different DESs as co-solvents at various DES concentrations, over wide ranges of temperatures at atmospheric pressure. This data bank includes 107 DES + water + drug/API systems in total. The solubility data were then modeled according to the solid-liquid equilibrium framework, using the local composition activity coefficient models of NRTL, and UNIQUAC. The results showed acceptable behavior with respect to the experimental values and trends for all of the investigated systems, with AARD% values of 9.65 % and 14.08 % for the NRTL and UNIQUAC models, respectively. In general, the lower errors of NRTL, as well as its simpler calculation process and the requirement of fewer component parameters, suggest the priority of NRTL over UNIQUAC for use in this field.

Evaluating ionic liquids for its potential as eco-friendly solvents for naproxen removal from water sources using COSMO-RS: Computational and experimental validation

An emerging contaminant of concern in aqueous streams is naproxen. Due to its poor solubility, non-biodegradability, and pharmaceutically active nature, the separation is challenging. Conventional solvents employed for naproxen are toxic and harmful. Ionic liquids (ILs) have attracted great attention as greener solubilizing and separating agent for various pharmaceuticals. ILs have found extensive usage as solvents in nanotechnological processes involving enzymatic reactions and whole cells. The employment of ILs can enhance the effectiveness and productivity of such bioprocesses. To avoid cumbersome experimental screening, in this study, conductor like screening model for real solvents (COSMO-RS) was used to screen ILs. Thirty anions and eight cations from various families were chosen. Activity coefficient at infinite dilution, capacity, selectivity, performance index, molecular interactions using σ-profiles and interaction energies were used to make predictions about solubility. According to the findings, quaternary ammonium cations, highly electronegative, and food-grade anions will form excellent ionic liquid combinations for solubilizing naproxen and hence will be better separating agents. This research will contribute easy designing of ionic liquid-based separation technologies for naproxen. In different separation technologies, ionic liquids can be employed as extractants, carriers, adsorbents, and absorbents.

Ionic Liquid-Based Green Emulsion Liquid Membrane for the Extraction of the Poorly Soluble Drug Ibuprofen

Ibuprofen (Ibf) is a biologically active drug (BADs) and an emerging contaminant of concern (CECs) in aqueous streams. Due to its adverse effects upon aquatic organisms and humans, the removal and recovery of Ibf are essential. Usually, conventional solvents are employed for the separation and recovery of ibuprofen. Due to environmental limitations, alternative green extracting agents need to be explored. Ionic liquids (ILs), emerging and greener alternatives, can also serve this purpose. It is essential to explore ILs that are effective for recovering ibuprofen, among millions of ILs. The conductor-like screening model for real solvents (COSMO-RS) is an efficient tool that can be used to screen ILs specifically for ibuprofen extraction. The main objective of this work was to identify the best IL for the extraction of ibuprofen. A total of 152 different cation-anion combinations consisting of eight aromatic and non-aromatic cations and nineteen anions were screened. The evaluation was based upon activity coefficients, capacity, and selectivity values. Furthermore, the effect of alkyl chain length was studied. The results suggest that quaternary ammonium (cation) and sulfate (anion) have better extraction ability for ibuprofen than the other combinations tested. An ionic liquid-based green emulsion liquid membrane (ILGELM) was developed using the selected ionic liquid as the extractant, sunflower oil as the diluent, Span 80 as the surfactant, and NaOH as the stripping agent. Experimental verification was carried out using the ILGELM. The experimental results indicated that the predicted COSMO-RS and the experimental results were in good agreement. The proposed IL-based GELM is highly effective for the removal and recovery of ibuprofen.

Combining environmental, health, and safety features with a conductor like Screening Model for selecting green solvents for antibiotic analyses

Extraction and chromatographic techniques for analyzing pharmaceutically active compounds necessitate large quantities of organic solvents, resulting in a high volume of hazardous waste. The concept of green solvents focuses on protecting the environment by reducing or even eliminating the use of toxic solvents. The main objective of this critical review article is to build a framework for choosing green solvents for antibiotic analyses. The article briefly discusses the chemical properties of ciprofloxacin, sulfamethoxazole, tetracycline, and trimethoprim, and the current state of methodologies for their analyses in water and wastewater. It evaluates the greenness of solvents used for antibiotic analyses and includes insights on the comparison between conventional and green solvents for the analyses. An economic and environmental health and safety analysis combined with a Conductor-like Screening Model for Real Solvent (COSMO-RS) molecular simulation technique for predicting extraction efficiency was used in the evaluation. Methyl acetate and propylene carbonate tied for the greenest solvents from an environmental and economic perspective, whereas the COSMO-RS approach suggests dimethyl sulfoxide (DMSO) as the most suitable candidate. Although DMSO ranked third environmentally and economically, after methyl acetate and propylene carbonate, it would be an ideal replacement of hazardous solvents if it could be manufactured at a lower cost. DMSO showed the highest extraction capacity, as it can interact with antibiotics through hydrophobic interaction and hydrogen bonding. This article can be used as a green solvent selection guide for developing sustainable processes for antibiotic analyses.

Experimental and Theoretical Study on Theobromine Solubility Enhancement in Binary Aqueous Solutions and Ternary Designed Solvents

The solubility of theobromine was studied both experimentally and theoretically. The solubility was determined spectrophotometrically at 25 °C in neat organic solvents, aqueous binary mixtures, Natural Deep Eutectic Solvents (NADES) and ternary NADES mixtures with water. It was found that addition of water in unimolar proportions with some organic solvents increases theobromine solubility compared to neat solvents. Additionally, using NADES results in a solubility increase of the studied compound not only in relation to water but also DMSO. The addition of water (0.2 molar fraction) to NADES is responsible for an even larger increase of solubility. The measured solubilities were interpreted in terms of three theoretical frameworks. The first one-belonging to the set of data reduction techniques-proved to be very efficient in quantitative back-computations of excess solubility of theobromine in all studied systems. The default approach utilizing the well-recognized COSMO-RS (Conductor-like Screening Model for Real Solvents) framework offered at most a qualitative solubility description. The extended search for possible contacts provided evidence for the existence of many intermolecular complexes that alter the electron density of the solute molecule, thus influencing solubility computations. Taking into account such intermolecular contacts by using the COSMO-RS-DARE (Conductor-like Screening Model for Realistic Solvation-Dimerization, Aggregation, and Reaction Extension) framework seriously increased the accuracy of solubility computations.

Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning

Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally studied binary systems, the one containing DMSO with water in unimolar proportions was found to be the most effective in theophylline dissolution. Likewise, for NADES, the addition of water (0.2 molar fraction) resulted in increased solubility compared to pure eutectics, with the highest solubilisation potential offered by the composition of choline chloride with glycerol. The ensemble of Statistica Automated Neural Networks (SANNs) developed using intermolecular interactions in pure systems has been found to be a very accurate model for solubility computations. This machine learning protocol was also applied as an extensive screening for potential solvents with higher solubility of theophylline. Such solvents were identified in all three subgroups, including neat solvents, binary mixtures and ternary NADES systems. Some methodological considerations of SANNs applications for future modelling were also provided. Although the developed protocol is focused exclusively on theophylline solubility, it also has general importance and can be used for the development of predictive models adequate for solvent screening of other compounds in a variety of systems. Formulation of such a model offers rational guidance for the selection of proper candidates as solubilisers in the designed solvents screening.

Optimization, thermodynamic characteristics and solubility predictions of natural deep eutectic solvents used for sulfonamide dissolution

The limited water solubility of sulfonamides provokes a search for new solvents offering not only increased solubility but also environmental and health safety. Therefore, six sulfonamides were studied in a series of natural deep eutectic solvents (NADES) comprising choline chloride with multi-hydroxyl compounds. Experimental screening aimed at finding the optimized NADES composition revealed that unimolar proportion of choline chloride and glycerol offers the highest solubility advantage, equal up to 43 times compared with water at 37 °C. Besides, quantum chemistry computations based on the COSMO-RS protocol were conducted in order to gain an insight into the thermodynamic characteristics of the systems and to explain the origin of the observed solubility increase. It was found that the factor responsible for the solubility gain in NADES are the interactions between choline chloride and sulfonamide drug molecules, having the highest affinities expressed in terms of Gibbs free energy of corresponding reactions. Finally, utilizing the obtained results together with artificial neural networks led to a perfect match between experimental and predicted solubility, documented by the mean absolute percentage error value below 2.5%. The developed protocol seems to be so general and accurate that screening of potential new API-NADES systems can be significantly simplified.

The Ionic Liquid Property Explorer: An Extensive Library of Task-Specific Solvents

Ionic liquids have a broad spectrum of applications ranging from gas separation to sensors and pharmaceuticals. Rational selection of the constituent ions is key to achieving tailor-made materials with functional properties. To facilitate the discovery of new ionic liquids for sustainable applications, we have created a virtual library of over 8 million synthetically feasible ionic liquids. Each structure has been evaluated for their-task suitability using data-driven statistical models calculated for 12 highly relevant properties: melting point, thermal decomposition, glass transition, heat capacity, viscosity, density, cytotoxicity, CO 2 solubility, surface tension, and electrical and thermal conductivity. For comparison, values of six properties computed using quantum chemistry based equilibrium thermodynamics COSMO-RS methods are also provided. We believe the data set will be useful for future efforts directed towards targeted synthesis and optimization.

Application of a computational model of natural deep eutectic solvents utilizing the COSMO-RS approach for screening of solvents with high solubility of rutin

The screening of natural deep eutectic solvents (NADES) to identify those with the ability to strongly solvate rutin was conducted using the COSMO-RS methodology. A NADES model was constructed that took into account the possible ionic and neutral forms of its constituents. The distributions of all forms were computed based on the equilibrium constants of neutralization reactions between amino and carboxylic acids. The proposed model was validated against the experimental solubilities of 15 NADES. A linear relationship between these data and the estimated activity coefficient values was found. The screening encompassed 126 different NADES. It was found that ten of them outperformed the best reference system. The most effective two-component solvent comprised proline combined with 2,3-diaminosuccinic acid, and the solubility of rutin in this solvent was found to be 130% greater than its solubility in the best reference system. The amino acids associated with the highest rutin solubilities were all cyclic, and the use of carboxylic acids with two carboxyl groups and a main chain consisting of two methylene groups with two amino substituents was observed to yield the best rutin solubilities. Because of the acidic properties of rutin, the presence of basic sites on the components of the NADES generally leads to enhanced solubility.

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).