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Solubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and antimicrobial agent. However, its low solubility hampers its efficient applications. In this project, deep eutectic solvents (DESs) were used as solubilizing agents for dapsone as an alternative to traditional solvents. DESs were composed of choline chloride and one of six polyols. Additionally, water-DES mixtures were studied as a type of ternary solvents. The solubility of dapsone in these systems was determined spectrophotometrically. This study also analyzed the intermolecular interactions, not only in the studied eutectic systems, but also in a wide range of systems found in the literature, determined using the COSMO-RS framework. The intermolecular interactions were quantified as affinity values, which correspond to the Gibbs free energy of pair formation of dapsone molecules with constituents of regular solvents and choline chloride-based deep eutectic solvents. The patterns of solute-solute, solute-solvent, and solvent-solvent interactions that affect solubility were recognized using Orange data mining software (version 3.36.2). Finally, the computed affinity values were used to provide useful descriptors for machine learning purposes. The impact of intermolecular interactions on dapsone solubility in neat solvents, binary organic solvent mixtures, and deep eutectic solvents was analyzed and highlighted, underscoring the crucial role of dapsone self-association and providing valuable insights into complex solubility phenomena. Also the importance of solvent-solvent diversity was highlighted as a factor determining dapsone solubility. The Non-Linear Support Vector Regression (NuSVR) model, in conjunction with unique molecular descriptors, revealed exceptional predictive accuracy. Overall, this study underscores the potency of computed molecular characteristics and machine learning models in unraveling complex molecular interactions, thereby advancing our understanding of solubility phenomena within the scientific community.
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Dapsona , Disolventes Eutécticos Profundos , Solubilidad , Solventes , Dapsona/química , Solventes/química , Disolventes Eutécticos Profundos/química , Agua/química , TermodinámicaRESUMEN
Deep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors. The results demonstrated that solvents based on choline chloride were more effective than those based on betaine. The optimal ratio of hydrogen bond acceptors to donors was found to be 1:2 molar. The addition of water to the DES resulted in a notable enhancement in the solubility of FA. Among the polyols tested, triethylene glycol was the most effective. Hence, DES composed of choline chloride and triethylene glycol (TEG) (1:2) with added water in a 0.3 molar ration is suggested as an efficient alternative to traditional organic solvents like DMSO. In the second part of this report, the affinities of FA in saturated solutions were computed for solute-solute and all solute-solvent pairs. It was found that self-association of FA leads to a cyclic structure of the C28 type, common among carboxylic acids, which is the strongest type of FA affinity. On the other hand, among all hetero-molecular bi-complexes, the most stable is the FA-TEG pair, which is an interesting congruency with the high solubility of FA in TEG containing liquids. Finally, this work combined COSMO-RS modeling with machine learning for the development of a model predicting ferulic acid solubility in a wide range of solvents, including not only DES but also classical neat and binary mixtures. A machine learning protocol developed a highly accurate model for predicting FA solubility, significantly outperforming the COSMO-RS approach. Based on the obtained results, it is recommended to use the support vector regressor (SVR) for screening new dissolution media as it is not only accurate but also has sound generalization to new systems.
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In this study, both practical and theoretical aspects of the solubility of edaravone (EDA) in Deep Eutectic Solvents (DESs) were considered. The solubility of edaravone in some media, including water, can be limited, which creates the need for new efficient and environmentally safe solvents. The solubility of EDA was measured spectrophotometrically and the complex intermolecular interactions within the systems were studied with the COSMO-RS framework. Of the four studied DES systems, three outperformed the most efficient classical organic solvent, namely dichloromethane, with the DES comprising choline chloride and triethylene glycol, acting as hydrogen bond donor (HBD), in a 1:2 molar proportion yielding the highest solubility of EDA. Interestingly, the addition of a specific amount of water further increased EDA solubility. Theoretical analysis revealed that in pure water or solutions with high water content, EDA stacking is responsible for self-aggregation and lower solubility. On the other hand, the presence of HBDs leads to the formation of intermolecular clusters with EDA, reducing self-aggregation. However, in the presence of a stoichiometric amount of water, a three-molecular EDA-HBD-water complex is formed, which explains why water can also act as a co-solvent. The high probability of formation of this type of complexes is related to the high affinity of the components, which exceeds all other possible complexes.
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Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental solubility data were collected for all DES systems. A machine learning model was developed using COSMO-RS molecular descriptors to predict solubility. All studied DESs exhibited a cosolvency effect, increasing drug solubility at modest concentrations of water. The model accurately predicted solubility for ibuprofen, ketoprofen, and related analogs (flurbiprofen, felbinac, phenylacetic acid, diphenylacetic acid). A machine learning approach utilizing COSMO-RS descriptors enables the rational design and solubility prediction of DES formulations for improved pharmaceutical applications.
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Disolventes Eutécticos Profundos , Ibuprofeno , Cetoprofeno , Aprendizaje Automático , Solubilidad , Cetoprofeno/química , Ibuprofeno/química , Disolventes Eutécticos Profundos/química , Inhibidores de la Ciclooxigenasa/química , Enlace de Hidrógeno , Solventes/químicaRESUMEN
BACKGROUND: Solubility is a fundamental physicochemical property of active pharmaceutical ingredients. The optimization of a dissolution medium aims not only to increase solubility and other aspects are to be included such as environmental impact, toxicity degree, availability, and costs. Obtaining comprehensive solubility characteristics of chemical compounds is a non-trivial and demanding process. Therefore, support from theoretical approaches is of practical importance. OBJECTIVES: This study aims to examine the accuracy of the reference solubility approach in the case of sulfanilamide dissolution in a variety of binary solvents. This pharmaceutically active substance has been extensively studied, and a substantial amount of solubility data is available. Unfortunately, using this set of data directly for theoretical modeling is impeded by noticeable inconsistencies in the published solubility data. Hence, this aspect is addressed by data curation using theoretical and experimental confirmations. MATERIAL AND METHODS: In the experimental part of our study, the popular shake-flask method combined with ultraviolet (UV) spectrophotometric measurements was applied for solubility determination. The computational phase utilized the conductor-like screening model for real solvents (COSMO-RS) approach. RESULTS: The analysis of the results of solubility calculations for sulfonamide in binary solvents revealed abnormally high error values for acetone-ethyl acetate mixtures, which were further confirmed with experimental measurements. Additional confirmation was obtained by extending the solubility measurements to a series of homologous acetate esters. CONCLUSIONS: Our study addresses the crucial issue of coherence of solubility data used for many theoretical inquiries, including parameter fitting of semi-empirical models, in-depth thermodynamic interpretations and application of machine learning protocols. The effectiveness of the proposed methodology for dataset curation was demonstrated for sulfanilamide solubility in binary mixtures. This approach enabled not only the formulation of a consistent dataset of sulfanilamide solubility binary solvent mixtures, but also its implementation as a qualitative tool guiding rationale solvent selection for experimental solubility screening.
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Solubilidad , Solventes , Sulfanilamida , Solventes/química , Sulfanilamida/química , Modelos Químicos , Sulfanilamidas/químicaRESUMEN
BACKGROUND: Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. OBJECTIVES: First, deep eutectic solvents (DES) were used as solubilizing agents for DAP as an alternative to traditional solvents. Second, intermolecular interactions in the systems were described and quantified. Finally, the solubility prediction model, previously created using the machine learning protocol, was extended and improved using new data obtained for eutectic systems. MATERIAL AND METHODS: New DES were created by blending choline chloride (ChCl) with 6 selected polyols. The solubility of DAP in these solvents was measured spectrophotometrically. The impact of water dilution on the solubility curve was investigated. Experimental research was enriched with theoretical interpretations of intermolecular interactions, identifying the most probable pairs in the systems. Dapsone self-association and its ability to interact with components of the analyzed systems were considered. Thermodynamic characteristics of pairs were utilized as molecular descriptors in the machine learning process, predicting solubility in both traditional organic solvents and the newly designed DES. RESULTS: The newly formulated solvents demonstrated significantly higher efficiency compared to traditional organic solvents, and a small addition of water increased solubility, indicating its role as a co-solvent. The interpretation of the mechanism of DAP solubility highlighted the competitive nature of self-association and pair formation. Thermodynamic parameters characterizing affinity were instrumental in developing an efficient model for theoretical screening across diverse solvent classes. The study emphasized the necessity of retraining models when introducing new experimental data, as exemplified by enriching the model with data from DES. CONCLUSIONS: The research showcased the efficacy of developing new DES for enhancing solubility and creating environmentally and pharmaceutically viable systems, using DAP as an example. Molecular interactions proved valuable in understanding solubility mechanisms and formulating predictive models through machine learning processes.
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Dapsona , Disolventes Eutécticos Profundos , Aprendizaje Automático , Solubilidad , Dapsona/química , Disolventes Eutécticos Profundos/química , Termodinámica , Solventes/químicaRESUMEN
Edaravone, acting as a cerebral protective agent, is administered to treat acute brain infarction. Its poor solubility is addressed here by means of optimizing the composition of the aqueous choline chloride (ChCl)-based eutectic solvents prepared with ethylene glycol (EG) or glycerol (GL) in the three different designed solvents compositions. The slurry method was used for spectroscopic solubility determination in temperatures between 298.15 K and 313.15 K. Measurements confirmed that ethaline (ETA = ChCl:EG = 1:2) and glyceline (GLE = ChCl:GL = 1:2) are very effective solvents for edaravone. The solubility at 298.15 K in the optimal compositions was found to be equal xE = 0.158 (cE = 302.96 mg/mL) and xE = 0.105 (cE = 191.06 mg/mL) for glyceline and ethaline, respectively. In addition, it was documented that wetting of neat eutectic mixtures increases edaravone solubility which is a fortunate circumstance not only from the perspective of a solubility advantage but also addresses high hygroscopicity of eutectic mixtures. The aqueous mixture with 0.6 mole fraction of the optimal composition yielded solubility values at 298.15 K equal to xE = 0.193 (cE = 459.69 mg/mL) and xE = 0.145 (cE = 344.22 mg/mL) for glyceline and ethaline, respectively. Since GLE is a pharmaceutically acceptable solvent, it is possible to consider this as a potential new liquid form of this drug with a tunable dosage. In fact, the recommended amount of edaravone administered to patients can be easily achieved using the studied systems. The observed high solubility is interpreted in terms of intermolecular interactions computed using the Conductor-like Screening Model for Real Solvents (COSMO-RS) approach and corrected for accounting of electron correlation, zero-point vibrational energy and basis set superposition errors. Extensive conformational search allowed for identifying the most probable contacts, the thermodynamic and geometric features of which were collected and discussed. It was documented that edaravone can form stable dimers stabilized via stacking interactions between five-membered heterocyclic rings. In addition, edaravone can act as a hydrogen bond acceptor with all components of the studied systems with the highest affinities to ion pairs of ETA and GLE. Finally, the linear regression model was formulated, which can accurately estimate edaravone solubility utilizing molecular descriptors obtained from COSMO-RS computations. This enables the screening of new eutectic solvents for finding greener replacers of designed solvents. The theoretical analysis of tautomeric equilibria confirmed that keto-isomer edaravone is predominant in the bulk liquid phase of all considered deep eutectic solvents (DES).
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This study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly developed Python code. To evaluate the models, a novel scoring function was formulated, considering not only the accuracy but also the bias-variance tradeoff through a learning curve analysis. An ensemble approach was adopted by selecting the top-performing regression models for test and validation subsets. The obtained model accurately back-calculated the experimental data and was used to predict the solubility of BSA in 2067 potential solvents. The analysis of the entire solvent space focused on the identification of solvents with high solubility, a low environmental impact, and affordability, leading to a refined list of potential candidates that meet all three requirements. The proposed procedure has general applicability and can significantly improve the quality and speed of experimental solvent screening.
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Modelos Químicos , Agua , Solventes , Análisis Costo-Beneficio , Solubilidad , BencenosulfonamidasRESUMEN
This study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called for an extension of the available pool of edaravone solubility data. Hence, new measurements were performed to collect edaravone solubility values in polar non-protic and diprotic media. Such an extended set of data was used in the machine learning process for tuning the parameters of regressor models and formulating the ensemble for predicting new data. In both phases, namely the model training and ensemble formulation, close attention was paid not only to minimizing the deviation of computed values from the experimental ones but also to ensuring high predictive power and accurate solubility computations for new systems. Furthermore, the environmental friendliness characteristics determined based on the common green solvent selection criteria, were included in the analysis. Our applied protocol led to the conclusion that the solubility space defined by ordinary solvents is limited, and it is unlikely to find solvents that are better suited for edaravone dissolution than those described in this manuscript. The theoretical framework presented in this study provides a precise guideline for conducting experiments, as well as saving time and resources in the pursuit of new findings.
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Solubility of active pharmaceutical ingredients is an important aspect of drug processing and formulation. Although caffeine was a subject of many studies aiming to quantify saturated solutions, many applied solvents suffer from not being environmentally friendly. This work fills this gap by presenting the results of solubility measurements in choline chloride natural deep eutectic solvents, ccNADES, comprising one of seven of the following polyalcohols: glycerol, sorbitol, xylitol, glucose, sucrose, maltose and fructose. The ratio of ccNADES components was optimized for maximizing caffeine solubility at room temperature. Additionally, temperature dependent solubility was measured for the first four systems exhibiting the highest solubility potential, both in their neat forms and in mixtures with water. Results were used for intermolecular interactions assessments using the COSMO-RS-DARE approach, which led to a perfect match between experimental and computed solubility values. An important methodological discussion was provided for an appropriate definition of the systems. Surprising linear trends were observed between the values of fitting parameters and water-ccNADES composition. In addition, comments on selection of the values of the fusion thermodynamic parameters were provided, which led to the conclusion that COSMO-RS-DARE solubility computations can effectively compensate for the inaccuracies of these important physicochemical properties.
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Colina , Disolventes Eutécticos Profundos , Cafeína , Colina/química , Solubilidad , Solventes/química , Agua/químicaRESUMEN
Coumarin is a naturally occurring lactone-type benzopyrone with various applications in the pharmaceutical, food, perfume, and cosmetics industries. This hydrophobic compound is poorly soluble in water but dissolves well in protic organic solvents such as alcohols. Despite the extensive use of coumarin, there are only a few reports documenting its solubility in organic solvents, and some reported data are incongruent, which was the direct impulse for this study. To resolve this problem, a theoretical congruency test was formulated using COSMO-RS-DARE for the determination of intermolecular interaction parameters, which allowed for the identification of outliers as suspicious datasets. The perfect match between back-computed values of coumarin solubility and the experimental ones confirms the reliability of the formulated theoretical approach and its adequacy for testing solubility data consistency. As the final approval, the temperature-related coumarin solubility in seven neat alcohols was determined experimentally. Four solvents (methanol, ethanol, 1-propanol, and 2-propanol) were used for reproducibility purposes, and an additional three (1-butanol, 1-pentanol, and 1-octanol) were used to extend the information on the homologous series. The consistency of this extended solubility dataset is discussed in terms of the comparison of remeasured solubility values with the ones already published and within the series of structurally similar solvents. The proposed procedure extends the range of applicability of COSMO-RS-DARE and provides a real and useful tool for consistency tests of already published solubility data, allowing for the approval/disapproval of existing data and filling gaps in datasets. Linear regressions utilizing a 2D molecular descriptor, SpMin2_Bhm, or the distance between solute and solvent in the Hansen solubility space, Ra, were formulated for the estimation of COMSO-RS-DARE integration parameters.
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Alcoholes , Modelos Químicos , Cumarinas , Reproducibilidad de los Resultados , Solubilidad , Solventes/químicaRESUMEN
Solubility is one of the most important physicochemical properties, both from a practical and theoretical perspective [...].
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Solventes , Solubilidad , Soluciones , Solventes/química , TermodinámicaRESUMEN
New protocol for screening efficient and environmentally friendly solvents was proposed and experimentally verified. The guidance for solvent selection comes from computed solubility via COSMO-RS approach. Furthermore, solute-solvent affinities computed using advanced quantum chemistry level were used as a rationale for observed solvents ranking. The screening protocol pointed out that 4-formylomorpholine (4FM) is an attractive solubilizer compared to commonly used aprotic solvents such as DMSO and DMF. This was tested experimentally by measuring the solubility of the title compounds in aqueous binary mixtures in the temperature range between 298.15 K and 313.15 K. Additional measurements were also performed for aqueous binary mixtures of DMSO and DMF. It has been found that the solubility of studied aromatic amides is very high and quite similar in all three aprotic solvents. For most aqueous binary mixtures, a significant decrease in solubility with a decrease in the organic fraction is observed, indicating that all systems can be regarded as efficient solvent-anti-solvent pairs. In the case of salicylamide dissolved in aqueous-4FM binary mixtures, a strong synergistic effect has been found leading to the highest solubility for 0.6 mole fraction of 4-FM.
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Dimetilsulfóxido , Salicilamidas , Benzamidas , Dimetilsulfóxido/química , Solventes/química , Agua/químicaRESUMEN
Chitosan-collagen blends have been widely applied in tissue engineering, joints diseases treatment, and many other biomedical fields. Understanding the affinity between chitosan and collagen type II is particularly relevant in the context of mechanical properties modulation, which is closely associated with designing biomaterials suitable for cartilage and synovial fluid regeneration. However, many structural features influence chitosan's affinity for collagen. One of the most important ones is the deacetylation degree (DD) in chitosan and the hydroxylation degree (HD) of proline (PRO) moieties in collagen. In this paper, combinations of both factors were analyzed using a very efficient molecular dynamics approach. It was found that DD and HD modifications significantly affect the structural features of the complex related to considered types of interactions, namely hydrogen bonds, hydrophobic, and ionic contacts. In the case of hydrogen bonds both direct and indirect (water bridges) contacts were examined. In case of the most collagen analogues, a very good correlation between binding free energy and DD was observed.
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Quitosano , Quitosano/química , Simulación de Dinámica Molecular , Colágeno Tipo II , Acetilación , Hidroxilación , ColágenoRESUMEN
In this study, the temperature-dependent solubility of nicotinamide (niacin) was measured in six neat solvents and five aqueous-organic binary mixtures (methanol, 1,4-dioxane, acetonitrile, DMSO and DMF). It was discovered that the selected set of organic solvents offer all sorts of solvent effects, including co-solvent, synergistic, and anti-solvent features, enabling flexible tuning of niacin solubility. In addition, differential scanning calorimetry was used to characterize the fusion thermodynamics of nicotinamide. In particular, the heat capacity change upon melting was measured. The experimental data were interpreted by means of COSMO-RS-DARE (conductor-like screening model for realistic solvation-dimerization, aggregation, and reaction extension) for concentration dependent reactions. The solute-solute and solute-solvent intermolecular interactions were found to be significant in all of the studied systems, which was proven by the computed mutual affinity of the components at the saturated conditions. The values of the Gibbs free energies of pair formation were derived at an advanced level of theory (MP2), including corrections for electron correlation and zero point vibrational energy (ZPE). In all of the studied systems the self-association of nicotinamide was found to be a predominant intermolecular complex, irrespective of the temperature and composition of the binary system. The application of the COSMO-RS-DARE approach led to a perfect match between the computed and measured solubility data, by optimizing the parameter of intermolecular interactions.
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Niacinamida/química , Termodinámica , Acetonitrilos , Rastreo Diferencial de Calorimetría , Cristalografía por Rayos X , Dimerización , Dimetilsulfóxido , Dimetilformamida , Dioxanos , Metanol , Modelos Químicos , Concentración Osmolar , Solubilidad , Soluciones , Solventes , Espectrofotometría Infrarroja , Temperatura , Vibración , AguaRESUMEN
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.
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Colina/química , Aprendizaje Automático , Modelos Químicos , Solventes/química , Teofilina/química , Agua/química , SolubilidadRESUMEN
The thermodynamic properties of phenacetin in solid state and in saturated conditions in neat and binary solvents were characterized based on differential scanning calorimetry and spectroscopic solubility measurements. The temperature-related heat capacity values measured for both the solid and melt states were provided and used for precise determination of the values for ideal solubility, fusion thermodynamic functions, and activity coefficients in the studied solutions. Factors affecting the accuracy of these values were discussed in terms of various models of specific heat capacity difference for phenacetin in crystal and super-cooled liquid states. It was concluded that different properties have varying sensitivity in relation to the accuracy of heat capacity values. The values of temperature-related excess solubility in aqueous binary mixtures were interpreted using the Jouyban-Acree solubility equation for aqueous binary mixtures of methanol, DMSO, DMF, 1,4-dioxane, and acetonitrile. All binary solvent systems studied exhibited strong positive non-ideal deviations from an algebraic rule of mixing. Additionally, an interesting co-solvency phenomenon was observed with phenacetin solubility in aqueous mixtures with acetonitrile or 1,4-dioxane. The remaining three solvents acted as strong co-solvents.
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Fenacetina/química , Solventes/química , Agua/química , Fenómenos Físicos , Solubilidad , Temperatura , TermodinámicaRESUMEN
PURPOSE: Study on curcumin dissolved in natural deep eutectic solvents (NADES) was aimed at exploiting their beneficial properties as drug carriers. METHODS: The concentration of dissolved curcumin in NADES was measured. Simulated gastrointestinal fluids were used to determine the concentration of curcumin and quantum chemistry computations were performed for clarifying the origin of curcumin solubility enhancement in NADES. RESULTS: NADES comprising choline chloride and glycerol had the highest potential for curcumin dissolution. This system was also successfully applied as an extraction medium for obtaining curcuminoids from natural sources, as well as an effective stabilizer preventing curcumin degradation from sunlight. The solubility of curcumin in simulated gastrointestinal fluids revealed that the significant increase of bioavailability takes place in the small intestinal fluid. CONCLUSIONS: Suspension of curcumin in NADES offers beneficial properties of this new liquid drug formulation starting from excreting from natural sources, through safe storage and ending on the final administration route. Therefore, there is a possibility of using a one-step process with this medium. The performed quantum chemistry computations clearly indicated the origin of the enhanced solubility of curcumin in NADES in the presence of intestinal fluids. Direct intermolecular contacts leading to hetero-molecular pairs with choline chloride and glycerol are responsible for elevating the bulk concentration of curcumin. Choline chloride plays a dominant role in the system and the complexes formed with curcumin are the most stable among all possible homo- and hetero-molecular pairs that can be found in NADES-curcumin systems.
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Colina/química , Curcumina/química , Portadores de Fármacos/química , Glicerol/química , Extractos Vegetales/química , Curcumina/administración & dosificación , Estabilidad de Medicamentos , Modelos Químicos , Teoría Cuántica , Solubilidad , Solventes , TermodinámicaRESUMEN
Objective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing this problem. Among such strategies, those that are environmentally and economically beneficial are of particular interest. Methods: The solubility of sulfanilamide and sulfacetamide in 21 different NADES compositions comprising choline chloride with sugars or sugar alcohols was measured spectrophotometrically. Thermodynamic parameters describing the studied systems were determined using the COSMO-RS computational protocol. Results: All of the considered NADES compositions gave an increase in solubility of the studied sulfonamides, with the highest solubilities obtained for the system comprising choline chloride and glycerol in unimolar proportions, which gave a solubility advantage of 83.7 and 73.8 for sulfanilamide and sulfacetamide, respectively. Theoretical studies indicated that the dissolution of both considered sulfonamides has a low endothermic character, with the lowest enthalpy values obtained for the most optimal, i.e. unimolar, proportions. The non-monotonous trend of enthalpy of dissolution was also discussed in terms of intermolecular interactions. Conclusions: The obtained results show the feasibility of using NADES as solubility enhancers for sulfonamides and encourage for further exploration in this field.
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Sulfacetamida/química , Sulfanilamida/química , Colina/química , Glicerol/química , Solubilidad , Solventes/químicaRESUMEN
The presented research focuses on the theoretical design and procedures for preparing protein conjugates with markers. For this purpose a series of phenanthroimidazole (PhI) analogous compounds was designed and investigated by means of first principle methods. Through the judicious choice of cross-linking reagents and the selection of reactive groups, five target fluorescent probes were selected, one of which was previously described using in vitro tests. For the best cognitive purpose and understanding of the nature of the protein conjugation, the studies describe the impact of the reactive group on the solvatochromism, the polarity of the charge transfer of the excited states, the Stokes' shift, ECD spectra and two-photon cross sections. The research is also extended to an analysis of PhI-Concanavalin A biocomplexes and changes in photophysical properties after conjugation. In order to identify valuable alternatives to commercial probes designed for cellular labelling in biological and biomedical imaging, biological properties were described such as ecotoxicity, log P and log BCF, and dye-protein binding was quantified by means of AutoDock and molecular dynamics simulations. The study showed that for phenanthroimidazole derivatives the factor which limits the possibility of their use in medical imaging is the presence of a pyridyl disulfide group, while the introduction of an N-hydroxysuccinimide ester may be used to create stable and valuable fluorescent probes with a wide spectrum for applications in biomedical imaging.