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

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.

Everything You Wanted to Know about Deep Eutectic Solvents but Were Afraid to Be Told

Are deep eutectic solvents (DESs) a promising alternative to conventional solvents? Perhaps, but their development is hindered by a plethora of misconceptions. These are carefully analyzed here, beginning with the very meaning of DESs, which has strayed far beyond its original scope of eutectic mixtures of Lewis or Brønsted acids and bases. Instead, a definition that is grounded on thermodynamic principles and distinguishes between eutectic and deep eutectic is encouraged, and the types of precursors that can be used to prepare DESs are reviewed. Landmark works surrounding the sustainability, stability, toxicity, and biodegradability of these solvents are also discussed, revealing piling evidence that numerous DESs reported thus far, particularly those that are choline based, lack sufficient sustainability-related traits to be considered green solvents. Finally, emerging DES applications are reviewed, emphasizing their most remarkable feature: the ability to liquefy a solid compound with a target property, allowing its use as a liquid solvent.

Insight into the glycerol extraction from biodiesel using deep eutectic solvents

CONTEXT

The main challenge of large-scale biofuel production is related to the extraction of its undesired impurities including glycerol, water, methanol, soap/catalyst, free fatty acids, glycerides, and others. There are many ways to remove glycerol, and herein, the one alternative is the extraction of glycerol from biodiesel by deep eutectic solvents. In this regard, the mixture of a choline chloride (ChCl) and urea, methyltriphenylphosphonium chloride (MTPPCl), and ethylene glycol (EGL), as a deep eutectic solvent (DES), is effective in removing glycerol from biofuel.

METHODS

In this work, we have investigated the formation mechanism of ChCl and urea, and then MTPPCl and EGL, as a DES, and then extraction of glycerol from biofuel via DES implementing density functional theory (DFT) by Gaussian09 software, B3LYP basis set, and classical all-atom molecular dynamics (MD) simulations by Gromacs software, GROMOS force field. DFT approximation demonstrates that Cl ion plays an important binding role in the formation of complexes ChCl/urea-based DES + biofuel and in MTPPCl/EGL-based DES + biofuel. We have also considered the formation and change of hydrogen bonds upon the formation of these systems using the DFT method. Large HOMO-LUMO gaps in ChCl/urea-based DES + biofuel and in MTPPCl/urea-based DES + biofuel demonstrate the stability of the complexes. The results of MD work have stated that the chloride ion formed bonding with the choline/ethylene glycol EGL, while still weakly intermolecular interacting with the urea/methyltriphenylphosphonium in ChCl/urea- and MTPPCl/EGL-based DESs. Further results of MD simulations stated that the DESs had a higher intermolecular interaction with glycerol in comparison with biofuel, thereby favoring the extraction process of glycerol from model biofuel.

HIGHLIGHTS

• Intermolecular interactions of choline chloride and urea, methyl triphenyl phosphonium chloride, and ethylene glycol-based DESs and their applications in the extraction of glycerol from biofuel studied by DFT calculations and classical all-atom molecular dynamics simulations. • Calculated outputs of DFT calculations and classical all-atom molecular dynamics simulations for DESs and their applications in the extraction of glycerol from biofuel were discussed in detail. • The molecular formation mechanism of choline and methyl triphenyl phosphonium-based DESs and their application in the extraction process of glycerol from biofuel were summarized.

Efficiency of Natural Deep Eutectic Solvents to Extract Phenolic Compounds from Agrimonia eupatoria: Experimental Study and In Silico Modelling

To replace common organic solvents that present inherent toxicity and have high volatility and to improve the extraction efficiency, a range of natural deep eutectic solvents (NADESs) were evaluated for the extraction of phenolic compounds from Agrimonia eupatoria. Screening of NADES efficiency was carried out based on the total phenolic and flavonoid content and radical-scavenging activity, determined by spectrophotometry, as well as phenolic compounds quantified, obtained using ultra-high-performance liquid chromatography with a diode array detector and a triple-quadrupole mass spectrometer. Increased extraction efficiency when compared with organic solvent was achieved using NADES mixtures choline chloride (ChCl):urea 1:2 and choline chloride:glycerol 1:1. Flavonol glycosides were the most abundant compounds in all extracts. The COSMO-RS model provided insights into the most important intermolecular interactions that drive the extraction process. Moreover, it could explain the extraction efficiency of flavonol glycosides using ChCl:glycerol NADES. The current article offers experimental evidence and mechanistic insights for the selection of optimal NADES to extract bioactive components from Agrimonia eupatoria.

A Simple Microextraction Method for Toxic Industrial Dyes Using a Fatty-Acid Solvent Mixture

A mixture of dodecanoic and hexanoic fatty acids was used to perform a simple and efficient microextraction method for industrial dyes such as methylene blue (MB), methyl violet (MV), and malachite green (MG) in aqueous solution. The fatty-acid microextractants were simply mixed and heated until the mixture became homogeneous before adding it to the dye solutions. The fatty-acid solvent and its components were characterized with Fourier transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H NMR) measurements, while the dye concentrations were measured using UV-Vis spectroscopy. The performance of the extracting mixture was observed to vary across different dye contaminants, dosages of the extractant, concentrations of the dyes, and contact times. High extraction efficiencies of up to ~99% were obtained for MG as well as MV, and ~73% efficiency was achieved for MB. The study shows how a mixture of fatty acids can be used as a simple, efficient, green, and sustainable low-volume method for the removal of toxic industrial dyes in aqueous solutions.

Multiple linear regression models for predicting the n‑octanol/water partition coefficients in the SAMPL7 blind challenge

A multiple linear regression model called MLR-3 is used for predicting the experimental n-octanol/water partition coefficient (log PN) of 22 N-sulfonamides proposed by the organizers of the SAMPL7 blind challenge. The MLR-3 method was trained with 82 molecules including drug-like sulfonamides and small organic molecules, which resembled the main functional groups present in the challenge dataset. Our model, submitted as "TFE-MLR", presented a root-mean-square error of 0.58 and mean absolute error of 0.41 in log P units, accomplishing the highest accuracy, among empirical methods and also in all submissions based on the ranked ones. Overall, the results support the appropriateness of multiple linear regression approach MLR-3 for computing the n-octanol/water partition coefficient in sulfonamide-bearing compounds. In this context, the outstanding performance of empirical methodologies, where 75% of the ranked submissions achieved root-mean-square errors < 1 log P units, support the suitability of these strategies for obtaining accurate and fast predictions of physicochemical properties as partition coefficients of bioorganic compounds.

Modeling the Physicochemical Properties of Natural Deep Eutectic Solvents

Natural deep eutectic solvents (NADES) are mixtures of naturally derived compounds with a significantly decreased melting point owing to specific interactions among the constituents. NADES have benign properties (low volatility, flammability, toxicity, cost) and tailorable physicochemical properties (by altering the type and molar ratio of constituents); hence, they are often considered to be a green alternative to common organic solvents. Modeling the relation between their composition and properties is crucial though, both for understanding and predicting their behavior. Several efforts have been made to this end. This Review aims at structuring the present knowledge as an outline for future research. First, the key properties of NADES are reviewed and related to their structure on the basis of the available experimental data. Second, available modeling methods applicable to NADES are reviewed. At the molecular level, DFT and molecular dynamics allow density differences and vibrational spectra to be interpreted, and interaction energies to be computed. Additionally, properties at the level of the bulk medium can be explained and predicted by semi-empirical methods based on ab initio methods (COSMO-RS) and equation of state models (PC-SAFT). Finally, methods based on large datasets are discussed: models based on group-contribution methods and machine learning. A combination of bulk-medium and dataset modeling allows qualitative prediction and interpretation of phase equilibria properties on the one hand, and quantitative prediction of melting point, density, viscosity, surface tension, and refractive index on the other. Multiscale modeling, combining molecular and macroscale methods, is expected to strongly enhance the predictability of NADES properties and their interaction with solutes, and thus yield truly tailorable solvents to accommodate (bio)chemical reactions.

Fast and Efficient Method to Evaluate the Potential of Eutectic Solvents to Dissolve Lignocellulosic Components

The application of eutectic solvents (ESs) in lignocellulosic biomass fractionation has been demonstrated as a promising approach to accomplish efficient and environmentally friendly biomass valorization. In general, ESs are a combination of two components, a hydrogen-bonding donor and a hydrogen-bonding acceptor, in which the melting point of the mixture is lower than that of the individual components. However, there are plenty of possible combinations to form ESs with the potential to apply in biomass processing. Therefore, the development of fast and effective screening methods to find combinations capable to dissolve the main biomass components—namely cellulose, hemicelluloses, and lignin—is highly required. An accurate and simple technique based on optical microscopy with or without polarized lenses was used in this study to quickly screen and monitor the dissolution of cellulose, xylose (a monomer of hemicelluloses), and lignin in several ESs. The dissolution of these solutes were investigated in different choline-chloride-based ESs (ChCl:UREA, ChCl:PROP, ChCl:EtGLY, ChCl:OXA, ChCl:GLY, ChCl:LAC). Small amounts of solute and solvent with temperature control were applied and the dissolution process was monitored in real time. The results obtained in this study showed that cellulose was insoluble in these ESs, while lignin and xylose were progressively dissolved.

Application of Deep Eutectic Solvents for the Extraction of Rutin and Rosmarinic Acid from Satureja montana L. and Evaluation of the Extracts Antiradical Activity

Satureja montana L. was used in the current research as the plant exhibits numerous health-promoting benefits due to its specific chemical composition. The extraction method based on deep eutectic solvents (DESs) was used for the extraction of rutin and rosmarinic acid from this plant. Five different choline chloride-based DESs with different volumes of water (10%, 30%, and 50% (v/v)) were used for the extraction at different temperatures (30, 50, and 70 °C) to investigate the influence on rosmarinic acid and rutin content obtained by high-performance liquid chromatography with diode-array detector (HPLC-DAD) in the obtained extracts. A principal component analysis was employed to explore and visualize the influence of applied parameters on the efficiency of the extraction procedure of rutin and rosmarinic acid. Among the tested DESs, choline chloride:lactic acid (mole ratio 1:2) and choline chloride:levulinic acid (mole ratio 1:2) were the most suitable for the extraction of rutin, while for rosmarinic acid choline chloride:urea (mole ratio 1:2) was the most effective solvent. The extract showing the best antiradical activity was obtained with choline chloride:urea (mole ratio 1:1) at 30 °C and 50% H₂O (v/v).

Tailor-made solvents for pharmaceutical use? Experimental and computational approach for determining solubility in deep eutectic solvents (DES)

A deep eutectic solvent (DES) is a mixture of two or more chemicals that interact via hydrogen bonding and has a melting point far below that of the individual components. DESs have been proposed as alternative solvents for poorly soluble active pharmaceutical ingredients (API). In this study, the solvation capacities of six deep eutectic solvents were compared to water and three conventional pharmaceutical solvents (PEG 300, ethanol and glycerol) for 11 APIs. The experimentally determined solubilities were compared to computational solubilities predicted by the Conductor-like Screening Model for Real Solvents (COSMO-RS). While the conventional pharmaceutical solvents PEG 300 and ethanol were the best solvents for the majority of the studied APIs, API-DES combinations were identified, which exceeded the API solubility found in the conventional pharmaceutical solvents. Furthermore, it was also possible to obtain high solubilities in the DESs relative to water, suggesting DESs to be potential solvents for poorly water soluble APIs. In addition, the relative increase in solubility found in the experimental data could be well predicted ab initio using COSMO-RS. Hence, COSMO-RS may in the future be used to reduce the experimental screening of potential DESs for a given API.

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.