This study examined the solubility of coumarin, a naturally occurring compound, in various alcohols using experimental and computational methods. Inconsistencies were found in literature solubility data for coumarin. The study developed a theoretical approach using COSMO-RS-DARE modeling to test solubility data consistency and identify outliers. Experimentally measured solubility data for coumarin in a series of alcohols matched the back-calculated COSMO-RS-DARE values, validating the theoretical approach. Linear regressions were also developed to correlate COSMO-RS-DARE integration parameters with molecular descriptors.
Finding the Right Solvent: A Novel Screening Protocol for Identifying Environ...Maciej Przybyłek
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.
Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures...Maciej Przybyłek
The solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen and phenacetin solubility data in neat and binary solvent mixtures was used for the development of a nonlinear deep machine learning model using new intuitive molecular descriptors derived from COSMO-RS computations. The literature dataset was augmented with results of new measurements in aqueous binary mixtures of 4-formylmorpholine, DMSO and DMF. The solubility values back-computed with the developed ensemble of neural networks are in perfect agreement with the experimental data, which enables the extensive screening of many combinations of solvents not studied experimentally within the applicability domain of the trained model. The final predictions were presented not only in the form of the set of optimal hyperparameters but also in a more intuitive way by the set of parameters of the Jouyban–Acree equation often used in the co-solvency domain. This new and effective approach is easily extendible to other systems, enabling the fast and reliable selection of candidates for new solvents and directing the experimental solubility screening of active pharmaceutical ingredients.
Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solven...Maciej Przybyłek
Dapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS: 112-57-2), and diethylene glycol bis(3-aminopropyl) ether (CAS: 4246-51-9). Furthermore, the study proposes the use of intermolecular interactions as molecular descriptors to predict the solubility of dapsone in neat solvents and binary mixtures using machine learning models. An ensemble of regressors was used, including support vector machines, random forests, gradient boosting, and neural networks. Affinities of dapsone to solvent molecules were calculated using COSMO-RS and used as input for model training. Due to the polymorphic nature of dapsone, fusion data are not available, which prohibits the direct use of COSMO-RS for solubility calculations. Therefore, a consonance solvent approach was tested, which allows an indirect estimation of the fusion properties. Unfortunately, the resulting accuracy is unsatisfactory. In contrast, the developed regressors showed high predictive potential. This work documents that intermolecular interactions characterized by solute–solvent contacts can be considered valuable molecular descriptors for solubility modeling and that the wealth of encoded information is sufficient for solubility predictions for new systems, including those for which experimental measurements of thermodynamic properties are unavailable.
New Screening Protocol for Effective Green Solvents Selection of Benzamide, S...Maciej Przybyłek
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.
Predicting sulfanilamide solubility in the binary mixtures using a reference ...Maciej Przybyłek
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.
Materials 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.
Application of Multivariate Adaptive Regression Splines (MARSplines) for Pred...Maciej Przybyłek
A new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard QSPR/QSAR internal validation procedures provided by the QSARINS software and by predicting the solubility classification of polymers and drug-like solid solutes in collections of solvents. By utilizing information derived only from SMILES strings, the obtained models allow for computing all of the three Hansen solubility parameters including dispersion, polarization, and hydrogen bonding. Although several descriptors are required for proper parameters estimation, the proposed procedure is simple and straightforward and does not require a molecular geometry optimization. The obtained HSP values are highly correlated with experimental data, and their application for solving solubility problems leads to essentially the same quality as for the original parameters. Based on provided models, it is possible to characterize any solvent and liquid solute for which HSP data are unavailable.
This document reports on an experimental study that measured distribution coefficients and diffusivities for 19 non-volatile solutes in 3 polymers. The study found that:
- Distribution coefficients ranged from near unity to several hundred and increased with vinyl acetate content in the polymers.
- Diffusion coefficients in EVAc copolymers ranged from 10-10 to 10-8 cm2/sec, much faster than 10-12 cm2/sec in PVAc.
- A long time (over 4-5 weeks) was required to reach equilibrium for solutes in PVAc, so diffusion models were used to calculate equilibrium values.
- Surface adsorption effects were found to be negligible.
Dissolution Enhancement of BCS Class 4 Dssrugs Using Quality by Design Approa...inventionjournals
Solid dispersion is one of the vastly accepted and practically economical processes in bioavailability enhancement study. The present investigation deals mostly with increase in solubility and dissolution rate of BCS class 4 drugs for enhancement of oral bioavailability. For the same solid dispersion were prepared and analyzed for appropriate concentration of drug polymer ratio by phase solubility analysis. The solvent evaporation study widely accepted due to its efficient solid dispersion in lesser efforts. The study designs were prepared with specific concentration of drug and polymer ratio with the help of high throughput model i.e. Central Composite Design (by Design Expert trial copy) by specific design of experiment with full factorial design (DOE). The fixed variables were concentration of polymers and dependant variables were dissolution and permeability across bio-membrane in in-vitro model. The prepared dispersion investigated for dissolution and permeability improvement using USP Type II apparatus and modified everted gut sac model which leads to improvement of quality of whole formulation with Quality by design efficiently.
Finding the Right Solvent: A Novel Screening Protocol for Identifying Environ...Maciej Przybyłek
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.
Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures...Maciej Przybyłek
The solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen and phenacetin solubility data in neat and binary solvent mixtures was used for the development of a nonlinear deep machine learning model using new intuitive molecular descriptors derived from COSMO-RS computations. The literature dataset was augmented with results of new measurements in aqueous binary mixtures of 4-formylmorpholine, DMSO and DMF. The solubility values back-computed with the developed ensemble of neural networks are in perfect agreement with the experimental data, which enables the extensive screening of many combinations of solvents not studied experimentally within the applicability domain of the trained model. The final predictions were presented not only in the form of the set of optimal hyperparameters but also in a more intuitive way by the set of parameters of the Jouyban–Acree equation often used in the co-solvency domain. This new and effective approach is easily extendible to other systems, enabling the fast and reliable selection of candidates for new solvents and directing the experimental solubility screening of active pharmaceutical ingredients.
Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solven...Maciej Przybyłek
Dapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS: 112-57-2), and diethylene glycol bis(3-aminopropyl) ether (CAS: 4246-51-9). Furthermore, the study proposes the use of intermolecular interactions as molecular descriptors to predict the solubility of dapsone in neat solvents and binary mixtures using machine learning models. An ensemble of regressors was used, including support vector machines, random forests, gradient boosting, and neural networks. Affinities of dapsone to solvent molecules were calculated using COSMO-RS and used as input for model training. Due to the polymorphic nature of dapsone, fusion data are not available, which prohibits the direct use of COSMO-RS for solubility calculations. Therefore, a consonance solvent approach was tested, which allows an indirect estimation of the fusion properties. Unfortunately, the resulting accuracy is unsatisfactory. In contrast, the developed regressors showed high predictive potential. This work documents that intermolecular interactions characterized by solute–solvent contacts can be considered valuable molecular descriptors for solubility modeling and that the wealth of encoded information is sufficient for solubility predictions for new systems, including those for which experimental measurements of thermodynamic properties are unavailable.
New Screening Protocol for Effective Green Solvents Selection of Benzamide, S...Maciej Przybyłek
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.
Predicting sulfanilamide solubility in the binary mixtures using a reference ...Maciej Przybyłek
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.
Materials 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.
Application of Multivariate Adaptive Regression Splines (MARSplines) for Pred...Maciej Przybyłek
A new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard QSPR/QSAR internal validation procedures provided by the QSARINS software and by predicting the solubility classification of polymers and drug-like solid solutes in collections of solvents. By utilizing information derived only from SMILES strings, the obtained models allow for computing all of the three Hansen solubility parameters including dispersion, polarization, and hydrogen bonding. Although several descriptors are required for proper parameters estimation, the proposed procedure is simple and straightforward and does not require a molecular geometry optimization. The obtained HSP values are highly correlated with experimental data, and their application for solving solubility problems leads to essentially the same quality as for the original parameters. Based on provided models, it is possible to characterize any solvent and liquid solute for which HSP data are unavailable.
This document reports on an experimental study that measured distribution coefficients and diffusivities for 19 non-volatile solutes in 3 polymers. The study found that:
- Distribution coefficients ranged from near unity to several hundred and increased with vinyl acetate content in the polymers.
- Diffusion coefficients in EVAc copolymers ranged from 10-10 to 10-8 cm2/sec, much faster than 10-12 cm2/sec in PVAc.
- A long time (over 4-5 weeks) was required to reach equilibrium for solutes in PVAc, so diffusion models were used to calculate equilibrium values.
- Surface adsorption effects were found to be negligible.
Dissolution Enhancement of BCS Class 4 Dssrugs Using Quality by Design Approa...inventionjournals
Solid dispersion is one of the vastly accepted and practically economical processes in bioavailability enhancement study. The present investigation deals mostly with increase in solubility and dissolution rate of BCS class 4 drugs for enhancement of oral bioavailability. For the same solid dispersion were prepared and analyzed for appropriate concentration of drug polymer ratio by phase solubility analysis. The solvent evaporation study widely accepted due to its efficient solid dispersion in lesser efforts. The study designs were prepared with specific concentration of drug and polymer ratio with the help of high throughput model i.e. Central Composite Design (by Design Expert trial copy) by specific design of experiment with full factorial design (DOE). The fixed variables were concentration of polymers and dependant variables were dissolution and permeability across bio-membrane in in-vitro model. The prepared dispersion investigated for dissolution and permeability improvement using USP Type II apparatus and modified everted gut sac model which leads to improvement of quality of whole formulation with Quality by design efficiently.
Computational chemistry is a branch of chemistry that uses computer simulation to assist in solving complex chemical problems. It exploits methods of theoretical chemistry, incorporated into efficient computer programs, to calculate the structures, the interactions, and the properties of molecules
This document summarizes a study that used group contribution methods to predict the solubility of volatile organic compounds (VOCs) in biodiesel. The study used three versions of the Universal Functional Activity Coefficient (UNIFAC) model to predict infinite dilution activity coefficients for VOCs in fatty acid methyl ester solvents that make up biodiesel. The results showed that activity coefficients decreased with increasing molecular weight for alkanes, amines, alkenes, organic acids, and alcohols. Shorter esters with lower carbon counts had higher activity coefficients than longer esters with higher carbon counts. Solubility of VOCs in biodiesel also decreased with increasing ester hydrocarbon unsaturation.
This document summarizes a study that used group contribution methods to predict vapor-liquid equilibrium (VLE) data for mixtures of volatile organic compounds (VOCs) and biodiesel. The study used the UNIFAC model and its modifications to predict infinite dilution activity coefficients for VOCs in biodiesel solvents at varying temperatures. The results showed that activity coefficients increased with temperature for alkanes, alcohols and acids/esters. Solubility of VOCs in biodiesel decreased with increasing biodiesel ester unsaturation and increased with increasing ester molecular weight.
Experimental and Theoretical Insights into the Intermolecular Interactions in...Maciej Przybyłek
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.
Intermolecular Interactions of Edaravone in Aqueous Solutions of Ethaline and...Maciej Przybyłek
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).
Deep Eutectic Solvents as Agents for Improving the Solubility of Edaravone: E...Maciej Przybyłek
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.
Crimson Publishers-Stable Labeled Isotopes as Internal Standards: A Critical ...CrimsonPublishersMAPP
SIL internal standards are commonly used in LC-MS/MS analyses to improve accuracy and precision. There are two main types: structurally similar analogs or isotopically labeled compounds containing stable isotopes like deuterium, carbon-13, or nitrogen-15. SIL standards provide structural information to understand analyte fragmentation patterns and metabolism. Their use has been shown to reduce ionization variations compared to analog standards. However, SIL standards can still cause ion suppression or enhancement and may not fully correct for matrix effects. While very useful, SIL standards also have limitations like expense and potential for different retention times versus analytes. Overall they remain a preferred choice but alternative standards may still be needed in some cases.
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Accepta...Maciej Przybyłek
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.
This document describes a new strategy for comprehensively analyzing polybrominated diphenyl ethers (PBDEs), polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and polychlorinated biphenyls (PCBs) using gas chromatography coupled with mass spectrometry. The method allows for the purification and fractionation of the target compound groups in a simple multi-step automated clean-up. The compounds are then analyzed using a single benchtop mass spectrometer in four separate injections. Electron impact ionization followed by tandem mass spectrometry provides the required sensitivity for environmental levels while maintaining selectivity, accuracy, and repeatability.
This document discusses the use of light scattering detection for analyzing biopharmaceutical proteins and antibodies. It provides background on the history and development of using light scattering with size exclusion chromatography and high performance liquid chromatography. The key applications discussed are determining absolute molecular weight, studying PEGylated proteins, characterizing protein-drug conjugates, and studying protein aggregation. Light scattering is presented as a powerful technique for characterization of biotherapeutics, with advantages over other methods like mass spectrometry in some applications. The document is divided into three parts, with the first part providing background on light scattering theory and applications.
Experimental and theoretical solubility advantage screening of bi-component s...Maciej Przybyłek
This document describes an experimental and theoretical study to screen potential solubilizers for curcumin. In the experimental phase, the solubility of curcumin was measured in binary mixtures with 24 excipients. The highest solubility enhancement was found with pyrogallol, caffeine, theophylline, and nicotinamide. A theoretical QSPR model was then developed using molecular descriptors to predict solubility. This model was applied to screen over 230,000 compounds and predict solubility for curcumin analogs and naturally occurring turmerones to identify new excipients.
The document discusses comparison of dissolution profiles through different methods and establishing an IVIVC (in vitro-in vivo correlation). It provides definitions of dissolution profile and objectives of comparing profiles. Various methods for comparing profiles are described, including graphical, statistical, and model-dependent/independent methods. Key factors for determining similarity between dissolution profiles using statistical methods like difference factor and similarity factor are outlined. The importance of developing an IVIVC to reduce costs and the need for bioavailability studies is also mentioned. A research article comparing different brands of metformin tablets using tests like dissolution rate, drug content and disintegration is briefly summarized.
The Utilization of 32 Full Factorial Design (FFD) for Optimization of Linco...Prachi Pandey
Objectives: The ongoing research aims to enhance the development of LNH-loaded nanogel by
utilizing DoE as the computational method to statistically validate their formulation.
Methodology: In this research Chitosan used as a natural polymer and Poly (Ethylene glycol)
[PEG] as a penetration or permeation enhancer. The different nanogel of LNH were synthesized
using the Nanoprecipitation and Dispersion method, with variations in the drug-polymer ratio
(1/0.03, 1/0.08, 1/0.12). The process parameters were carefully optimizing for enhance the
efficiency of the synthesis. To achieve this, optimization studies were conducted using 3² FFD,
employing the Design Expert Software Trial version 10.0.7. The total of 13 runs were generated to
ensure comprehensive analysis and evaluation of the procedure. The selected independent
variables included the concentration of Chitosan (R1) and Carbopol 934 (R2). The dependent
variables, on the other hand, were particle size (P1), Polydispersity Index (P2), and % Drug release
(P3), chosen in that order. By employing this optimization technique, one can acquire valuable
information in a manner that is both efficient and cost-effective. This approach facilitates a deeper
comprehension of the relationship between controllable independent variables and the performance
and quality of the Nanogels being produced
The Utilization of 32 Full Factorial Design (FFD) for Optimization of Linco...RAHUL PAL
Objectives: The ongoing research aims to enhance the development of LNH-loaded nanogel by
utilizing DoE as the computational method to statistically validate their formulation.
Methodology: In this research Chitosan used as a natural polymer and Poly (Ethylene glycol)
[PEG] as a penetration or permeation enhancer. The different nanogel of LNH were synthesized
using the Nanoprecipitation and Dispersion method, with variations in the drug-polymer ratio
(1/0.03, 1/0.08, 1/0.12). The process parameters were carefully optimizing for enhance the
efficiency of the synthesis. To achieve this, optimization studies were conducted using 3² FFD,
employing the Design Expert Software Trial version 10.0.7. The total of 13 runs were generated to
ensure comprehensive analysis and evaluation of the procedure. The selected independent
variables included the concentration of Chitosan (R1) and Carbopol 934 (R2). The dependent
variables, on the other hand, were particle size (P1), Polydispersity Index (P2), and % Drug release
(P3), chosen in that order. By employing this optimization technique, one can acquire valuable
information in a manner that is both efficient and cost-effective. This approach facilitates a deeper
comprehension of the relationship between controllable independent variables and the performance
and quality of the Nanogels being produced.
Some physicochemical properties such as density, refractive index, solubility, conductance, dissociation constant etc. have been studied for some newly synthesized chalcones in different solvents at 308.15 K.
The document discusses various topics related to drug design and discovery including structure-based drug design, quantitative structure-activity relationships (QSAR), molecular docking, and de novo drug design. It provides details on the drug discovery process, strategies for structure-based design including pharmacophore identification and docking simulations, factors that govern drug design such as physicochemical properties, and methods for QSAR model development, validation, and applications in drug design.
Physicochemical Profiling In Drug ResearchBrian Bissett
Physicochemical and Biological Profiling in Drug Research ElogD(7.4) 20,000 Compounds Later: Refinements, Observations and Applications
Franco Lombardo, Marina Y. Shalaeva, Brian D. Bissett and Natalya Chistokhodova.
Molecular Properties Group, PGRD Groton Laboratories, Groton, CT 06340, U.S.A.
1) Molecular simulations were used to analyze the mode of inhibition of three pesticides (baygon, metacrate, and velpar) on firefly luciferase. The simulations revealed that the pesticides share the same binding site in the luciferin pocket of luciferase.
2) Experiments were conducted to determine the toxicities of the three individual pesticides and 15 binary mixtures on firefly luciferase bioluminescence. Concentration addition modeling was able to predict the toxicities of the mixtures based on the molecular simulation results.
3) There was a linear relationship found between the calculated binding free energy of the mixtures from the individual pesticide components, and the median effective concentrations of the mixtures in experiments.
This document summarizes and compares three models (Dubinin–Stoeckli, Stoeckli, and Horvath–Kawazoe) for determining the pore-size distribution of activated carbons from adsorption isotherm data. It studies the effects of two different chemical activation agents (potassium hydroxide and zinc chloride) and their ratios on the porosity and pore-size distribution of activated carbons derived from macadamia nutshells. The results from the three models are generally comparable, though some differences exist due to their different underlying assumptions. Zinc chloride-activated carbons showed higher adsorption capacity than potassium hydroxide-activated ones at the same chemical ratio. Pore
Effect of Nanohydroxyapatite on Silk Fibroin–Chitosan Interactions—Molecular ...Maciej Przybyłek
Fibroin–chitosan composites, especially those containing nanohydroxyapatite, show potential for bone tissue regeneration. The physicochemical properties of these biocomposites depend on the compatibility between their components. In this study, the intermolecular interactions of fibroin and chitosan were analyzed using a molecular dynamics approach. Two types of systems were investigated: one containing acetic acid and the other containing calcium (Ca2+) and hydrogen phosphate (HPO₄2−) ions mimicking hydroxyapatite conditions. After obtaining the optimal equilibrium structures, the distributions of several types of interactions, including hydrogen bonds, ionic contacts, and hydrophobic contacts, along with structural and energetical features, were examined. The calculated binding energy values for the fibroin–chitosan complexes confirm their remarkable stability. The high affinity of fibroin for chitosan can be explained by the formation of a dense network of interactions between the considered biopolymers. These interactions were found to primarily be hydrogen bonds and ionic contacts involving ALA, ARG, ASN, ASP, GLN, GLU, GLY, LEU, PRO, SER, THR, TYR, and VAL residues. As established, the complexation of fibroin with chitosan maintains the β-sheet conformation of the peptide. β-Sheet fragments in fibroin are involved in the formation of a significant number of hydrogen bonds and ionic contacts with chitosan.
Molecular dynamics simulations of the affinity of chitin and chitosan for col...Maciej Przybyłek
Chitosan and chitin are promising biopolymers used in many areas including biomedical applications, such as tissue engineering and viscosupplementation. Chitosan shares similar properties with hyaluronan, a natural component of synovial fluid, making it a good candidate for joint disease treatment. The structural and energetic consequences of intermolecular interactions are crucial for understanding the biolubrication phenomenon and other important biomedical features. However, the properties of biopolymers, including their complexation abilities, are influenced by the nature of the aqueous medium with which they interact. In this study, we employed molecular dynamics simulations to describe the effect of pH and the presence of sodium and calcium cations on the stability of molecular complexes formed by collagen type II with chitin and chitosan oligosaccharides. Based on Gibbs free energy of binding, all considered complexes are thermodynamically stable over the entire pH range. The affinity between chitosan oligosaccharide and collagen is highly influenced by pH, while oligomeric chitin shows no pH-dependent effect on the stability of molecular assemblies with collagen. On the other hand, the presence of sodium and calcium cations has a negligible effect on the affinity of chitin and chitosan for collagen.
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This document summarizes a study that used group contribution methods to predict the solubility of volatile organic compounds (VOCs) in biodiesel. The study used three versions of the Universal Functional Activity Coefficient (UNIFAC) model to predict infinite dilution activity coefficients for VOCs in fatty acid methyl ester solvents that make up biodiesel. The results showed that activity coefficients decreased with increasing molecular weight for alkanes, amines, alkenes, organic acids, and alcohols. Shorter esters with lower carbon counts had higher activity coefficients than longer esters with higher carbon counts. Solubility of VOCs in biodiesel also decreased with increasing ester hydrocarbon unsaturation.
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Experimental and Theoretical Insights into the Intermolecular Interactions in...Maciej Przybyłek
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.
Intermolecular Interactions of Edaravone in Aqueous Solutions of Ethaline and...Maciej Przybyłek
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).
Deep Eutectic Solvents as Agents for Improving the Solubility of Edaravone: E...Maciej Przybyłek
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.
Crimson Publishers-Stable Labeled Isotopes as Internal Standards: A Critical ...CrimsonPublishersMAPP
SIL internal standards are commonly used in LC-MS/MS analyses to improve accuracy and precision. There are two main types: structurally similar analogs or isotopically labeled compounds containing stable isotopes like deuterium, carbon-13, or nitrogen-15. SIL standards provide structural information to understand analyte fragmentation patterns and metabolism. Their use has been shown to reduce ionization variations compared to analog standards. However, SIL standards can still cause ion suppression or enhancement and may not fully correct for matrix effects. While very useful, SIL standards also have limitations like expense and potential for different retention times versus analytes. Overall they remain a preferred choice but alternative standards may still be needed in some cases.
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Accepta...Maciej Przybyłek
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.
This document describes a new strategy for comprehensively analyzing polybrominated diphenyl ethers (PBDEs), polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and polychlorinated biphenyls (PCBs) using gas chromatography coupled with mass spectrometry. The method allows for the purification and fractionation of the target compound groups in a simple multi-step automated clean-up. The compounds are then analyzed using a single benchtop mass spectrometer in four separate injections. Electron impact ionization followed by tandem mass spectrometry provides the required sensitivity for environmental levels while maintaining selectivity, accuracy, and repeatability.
This document discusses the use of light scattering detection for analyzing biopharmaceutical proteins and antibodies. It provides background on the history and development of using light scattering with size exclusion chromatography and high performance liquid chromatography. The key applications discussed are determining absolute molecular weight, studying PEGylated proteins, characterizing protein-drug conjugates, and studying protein aggregation. Light scattering is presented as a powerful technique for characterization of biotherapeutics, with advantages over other methods like mass spectrometry in some applications. The document is divided into three parts, with the first part providing background on light scattering theory and applications.
Experimental and theoretical solubility advantage screening of bi-component s...Maciej Przybyłek
This document describes an experimental and theoretical study to screen potential solubilizers for curcumin. In the experimental phase, the solubility of curcumin was measured in binary mixtures with 24 excipients. The highest solubility enhancement was found with pyrogallol, caffeine, theophylline, and nicotinamide. A theoretical QSPR model was then developed using molecular descriptors to predict solubility. This model was applied to screen over 230,000 compounds and predict solubility for curcumin analogs and naturally occurring turmerones to identify new excipients.
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The Utilization of 32 Full Factorial Design (FFD) for Optimization of Linco...Prachi Pandey
Objectives: The ongoing research aims to enhance the development of LNH-loaded nanogel by
utilizing DoE as the computational method to statistically validate their formulation.
Methodology: In this research Chitosan used as a natural polymer and Poly (Ethylene glycol)
[PEG] as a penetration or permeation enhancer. The different nanogel of LNH were synthesized
using the Nanoprecipitation and Dispersion method, with variations in the drug-polymer ratio
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efficiency of the synthesis. To achieve this, optimization studies were conducted using 3² FFD,
employing the Design Expert Software Trial version 10.0.7. The total of 13 runs were generated to
ensure comprehensive analysis and evaluation of the procedure. The selected independent
variables included the concentration of Chitosan (R1) and Carbopol 934 (R2). The dependent
variables, on the other hand, were particle size (P1), Polydispersity Index (P2), and % Drug release
(P3), chosen in that order. By employing this optimization technique, one can acquire valuable
information in a manner that is both efficient and cost-effective. This approach facilitates a deeper
comprehension of the relationship between controllable independent variables and the performance
and quality of the Nanogels being produced
The Utilization of 32 Full Factorial Design (FFD) for Optimization of Linco...RAHUL PAL
Objectives: The ongoing research aims to enhance the development of LNH-loaded nanogel by
utilizing DoE as the computational method to statistically validate their formulation.
Methodology: In this research Chitosan used as a natural polymer and Poly (Ethylene glycol)
[PEG] as a penetration or permeation enhancer. The different nanogel of LNH were synthesized
using the Nanoprecipitation and Dispersion method, with variations in the drug-polymer ratio
(1/0.03, 1/0.08, 1/0.12). The process parameters were carefully optimizing for enhance the
efficiency of the synthesis. To achieve this, optimization studies were conducted using 3² FFD,
employing the Design Expert Software Trial version 10.0.7. The total of 13 runs were generated to
ensure comprehensive analysis and evaluation of the procedure. The selected independent
variables included the concentration of Chitosan (R1) and Carbopol 934 (R2). The dependent
variables, on the other hand, were particle size (P1), Polydispersity Index (P2), and % Drug release
(P3), chosen in that order. By employing this optimization technique, one can acquire valuable
information in a manner that is both efficient and cost-effective. This approach facilitates a deeper
comprehension of the relationship between controllable independent variables and the performance
and quality of the Nanogels being produced.
Some physicochemical properties such as density, refractive index, solubility, conductance, dissociation constant etc. have been studied for some newly synthesized chalcones in different solvents at 308.15 K.
The document discusses various topics related to drug design and discovery including structure-based drug design, quantitative structure-activity relationships (QSAR), molecular docking, and de novo drug design. It provides details on the drug discovery process, strategies for structure-based design including pharmacophore identification and docking simulations, factors that govern drug design such as physicochemical properties, and methods for QSAR model development, validation, and applications in drug design.
Physicochemical Profiling In Drug ResearchBrian Bissett
Physicochemical and Biological Profiling in Drug Research ElogD(7.4) 20,000 Compounds Later: Refinements, Observations and Applications
Franco Lombardo, Marina Y. Shalaeva, Brian D. Bissett and Natalya Chistokhodova.
Molecular Properties Group, PGRD Groton Laboratories, Groton, CT 06340, U.S.A.
1) Molecular simulations were used to analyze the mode of inhibition of three pesticides (baygon, metacrate, and velpar) on firefly luciferase. The simulations revealed that the pesticides share the same binding site in the luciferin pocket of luciferase.
2) Experiments were conducted to determine the toxicities of the three individual pesticides and 15 binary mixtures on firefly luciferase bioluminescence. Concentration addition modeling was able to predict the toxicities of the mixtures based on the molecular simulation results.
3) There was a linear relationship found between the calculated binding free energy of the mixtures from the individual pesticide components, and the median effective concentrations of the mixtures in experiments.
This document summarizes and compares three models (Dubinin–Stoeckli, Stoeckli, and Horvath–Kawazoe) for determining the pore-size distribution of activated carbons from adsorption isotherm data. It studies the effects of two different chemical activation agents (potassium hydroxide and zinc chloride) and their ratios on the porosity and pore-size distribution of activated carbons derived from macadamia nutshells. The results from the three models are generally comparable, though some differences exist due to their different underlying assumptions. Zinc chloride-activated carbons showed higher adsorption capacity than potassium hydroxide-activated ones at the same chemical ratio. Pore
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Effect of Nanohydroxyapatite on Silk Fibroin–Chitosan Interactions—Molecular ...Maciej Przybyłek
Fibroin–chitosan composites, especially those containing nanohydroxyapatite, show potential for bone tissue regeneration. The physicochemical properties of these biocomposites depend on the compatibility between their components. In this study, the intermolecular interactions of fibroin and chitosan were analyzed using a molecular dynamics approach. Two types of systems were investigated: one containing acetic acid and the other containing calcium (Ca2+) and hydrogen phosphate (HPO₄2−) ions mimicking hydroxyapatite conditions. After obtaining the optimal equilibrium structures, the distributions of several types of interactions, including hydrogen bonds, ionic contacts, and hydrophobic contacts, along with structural and energetical features, were examined. The calculated binding energy values for the fibroin–chitosan complexes confirm their remarkable stability. The high affinity of fibroin for chitosan can be explained by the formation of a dense network of interactions between the considered biopolymers. These interactions were found to primarily be hydrogen bonds and ionic contacts involving ALA, ARG, ASN, ASP, GLN, GLU, GLY, LEU, PRO, SER, THR, TYR, and VAL residues. As established, the complexation of fibroin with chitosan maintains the β-sheet conformation of the peptide. β-Sheet fragments in fibroin are involved in the formation of a significant number of hydrogen bonds and ionic contacts with chitosan.
Molecular dynamics simulations of the affinity of chitin and chitosan for col...Maciej Przybyłek
Chitosan and chitin are promising biopolymers used in many areas including biomedical applications, such as tissue engineering and viscosupplementation. Chitosan shares similar properties with hyaluronan, a natural component of synovial fluid, making it a good candidate for joint disease treatment. The structural and energetic consequences of intermolecular interactions are crucial for understanding the biolubrication phenomenon and other important biomedical features. However, the properties of biopolymers, including their complexation abilities, are influenced by the nature of the aqueous medium with which they interact. In this study, we employed molecular dynamics simulations to describe the effect of pH and the presence of sodium and calcium cations on the stability of molecular complexes formed by collagen type II with chitin and chitosan oligosaccharides. Based on Gibbs free energy of binding, all considered complexes are thermodynamically stable over the entire pH range. The affinity between chitosan oligosaccharide and collagen is highly influenced by pH, while oligomeric chitin shows no pH-dependent effect on the stability of molecular assemblies with collagen. On the other hand, the presence of sodium and calcium cations has a negligible effect on the affinity of chitin and chitosan for collagen.
Collagen Type II—Chitosan Interactions as Dependent on Hydroxylation and Acet...Maciej Przybyłek
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.
Albumin–Hyaluronan Interactions: Influence of Ionic Composition Probed by Mol...Maciej Przybyłek
The lubrication mechanism in synovial fluid and joints is not yet fully understood. Nevertheless,
intermolecular interactions between various neutral and ionic species including large
macromolecular systems and simple inorganic ions are the key to understanding the excellent lubrication
performance. An important tool for characterizing the intermolecular forces and their
structural consequences is molecular dynamics. Albumin is one of the major components in synovial
fluid. Its electrostatic properties, including the ability to form molecular complexes, are closely
related to pH, solvation, and the presence of ions. In the context of synovial fluid, it is relevant to
describe the possible interactions between albumin and hyaluronate, taking into account solution
composition effects. In this study, the influence of Na+, Mg2+, and Ca2+ ions on human serum
albumin–hyaluronan interactions were examined using molecular dynamics tools. It was established
that the presence of divalent cations, and especially Ca2+, contributes mostly to the increase of
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negatively charged hyaluronan and albumin. Furthermore, the most probable binding sites were
structurally and energetically characterized. The indicated moieties exhibit a locally positive charge
which enables hyaluronate binding (direct and water mediated).
Effect of Chitosan Deacetylation on Its Affinity to Type III Collagen: A Mole...Maciej Przybyłek
The ability to form strong intermolecular interactions by linear glucosamine polysaccharides with collagen is strictly related to their nonlinear dynamic behavior and hence bio-lubricating features. Type III collagen plays a crucial role in tissue regeneration, and its presence in the articular cartilage affects its bio-technical features. In this study, the molecular dynamics methodology was applied to evaluate the effect of deacetylation degree on the chitosan affinity to type III collagen. The computational procedure employed docking and geometry optimizations of different chitosan structures characterized by randomly distributed deacetylated groups. The eight different degrees of deacetylation from 12.5% to 100% were taken into account. We found an increasing linear trend (R2 = 0.97) between deacetylation degree and the collagen-chitosan interaction energy. This can be explained by replacing weak hydrophobic contacts with more stable hydrogen bonds involving amino groups in N-deacetylated chitosan moieties. In this study, the properties of chitosan were compared with hyaluronic acid, which is a natural component of synovial fluid and cartilage. As we found, when the degree of deacetylation of chitosan was greater than 0.4, it exhibited a higher affinity for collagen than in the case of hyaluronic acid.
Predicting Value of Binding Constants of Organic Ligands to Beta-Cyclodextrin...Maciej Przybyłek
The quantitative structure–activity relationship (QSPR) model was formulated to quantify values of the binding constant (lnK) of a series of ligands to beta–cyclodextrin (β-CD). For this purpose, the multivariate adaptive regression splines (MARSplines) methodology was adopted with molecular descriptors derived from the simplified molecular input line entry specification (SMILES) strings. This approach allows discovery of regression equations consisting of new non-linear components (basis functions) being combinations of molecular descriptors. The model was subjected to the standard internal and external validation procedures, which indicated its high predictive power. The appearance of polarity-related descriptors, such as XlogP, confirms the hydrophobic nature of the cyclodextrin cavity. The model can be used for predicting the affinity of new ligands to β-CD. However, a non-standard application was also proposed for classification into Biopharmaceutical Classification System (BCS) drug types. It was found that a single parameter, which is the estimated value of lnK, is sufficient to distinguish highly permeable drugs (BCS class I and II) from low permeable ones (BCS class II and IV). In general, it was found that drugs of the former group exhibit higher affinity to β-CD then the latter group (class III and IV).
Natural Deep Eutectic Solvents as Agents for Improving Solubility, Stability ...Maciej Przybyłek
This research paper studied the use of natural deep eutectic solvents (NADES) to improve the solubility, stability, and delivery of curcumin. The study found that NADES composed of choline chloride and glycerol had the highest solubility for curcumin. This NADES system was also effective at extracting curcuminoids from turmeric and preventing degradation of curcumin when exposed to sunlight. Testing in simulated gastrointestinal fluids showed a significant increase in curcumin bioavailability in the small intestine. Quantum chemistry computations indicated that direct molecular interactions between curcumin and choline chloride or glycerol were responsible for enhancing curcumin's solubility in NADES, especially
Utilization of oriented crystal growth for screening of aromatic carboxylic a...Maciej Przybyłek
The possibility of molecular complex formation in the solid state of urea with benzoic acid analogues was measured directly on the crystallite films deposited on the glass surface using powder X-ray diffractometry (PXRD). Obtained solid mixtures were also analyzed using Fourier transform infrared spectroscopy (FTIR). The simple droplet evaporation method was found to be efficient, robust, fast and cost-preserving approach for first stage cocrystal screening. Additionally, the application of orientation effect to cocrystal screening simplifies the analysis due to damping of majority of diffraction signals coming from coformers. During validation phase the proposed approach successfully reproduced both positive cases of cocrystallization (urea:salicylic acid and urea:4-hydroxy benzoic acid) as well as pairs of co-formers immiscible in the solid state (urea:benzoic acid and urea:acetylsalicylic acids). Based on validated approach new cocrystals of urea were identified in complexes with 3-hydroxybenzoic acid, 2,4-dihydroxybenzoic acid, 2,5-dihydroxybenzoic acid, 2,6-dihydroxybenzoic acid and 3,5-dihydroxybenzoic acid. In all cases formation of multicomponent crystal phase was confirmed by the appearance of new reflexes on the diffraction patterns and FTIR absorption band shifts of O–H and N–H groups.
Studies on the formation of formaldehyde during 2-ethylhexyl 4-(dimethylamino...Maciej Przybyłek
In order to protect the skin from UV radiation, personal care products (PCPS) often contain chemical UV-filters. These compounds can enter the environment causing serious consequences on the water ecosystems. The aim of this study was to examine, the effect of different factors, such as UV light, the presence of NaOCl and H2O2 on the formaldehyde formation during popular UV filter, 2-ethylhexyl 4-(dimethylamino)benzoate (ODPABA) demethylation. The concentration of formaldehyde was determined by VIS spectrophotometry after derivatization. The reaction mixtures were qualitatively analyzed using GC/MS chromatography. The highest concentration of formaldehyde was observed in the case of ODPABA/H2O2/UV reaction mixture. In order to describe two types of demethylation mechanisms, namely, radical and ionic, the experimental results were enriched with Fukui function analysis and thermodynamic calculations. In the case of non-irradiated system containing ODPABA and NaOCl, demethylation reaction probably proceeds via ionic mechanism. As it was established, amino nitrogen atom in the ODPABA molecule is the most susceptible site for the HOCl electrophilic attack, which is the first step of ionic demethylation mechanism. In the case of irradiated mixtures, the reaction is probably radical in nature. The results of thermodynamic calculations showed that abstraction of the hydrogen from N(CH3)2 group is more probable than from 2-ethylhexyl moiety, which indicates higher susceptibility of N(CH3)2 to the oxidation.
Reaction of aniline with ammonium persulphate and concentrated hydrochloric a...Maciej Przybyłek
In this paper, the reaction of aniline with ammonium persulphate and concentrated HCl was studied. As a result of our experimental studies, 2,4,6-trichlorophenylamine was identified as the main product. This shows that a high concentration of HCl does not favour oxidative polymerisation of phenylamine, even though the ammonium persulphate/HCl system is widely used in polyaniline synthesis. On the basis of the experimental data and density functional theory for reaction path modelling, we proposed a mechanism for oxidative chlorination of aniline. We assumed that this reaction proceeded in three cyclically repeated steps; protonation of aniline, formation of singlet ground state phenylnitrenium cation, and nucleophilic substitution. In order to confirm this mechanism, kinetic, thermochemical, and natural bond orbital population analyses were performed.
Propensity of salicylamide and ethenzamide cocrystallization with aromatic ca...Maciej Przybyłek
The cocrystallization of salicylamide (2-hydroxybenzamide, SMD) and ethenzamide (2-ethoxybenzamide, EMD) with aromatic carboxylic acids was examined both experimentally and theoretically. The supramolecular synthesis taking advantage of the droplet evaporative crystallization (DEC) technique was combined with powder diffraction and vibrational spectroscopy as the analytical tools. This led to identification of eleven new cocrystals including pharmaceutically relevant coformers such as mono- and dihydroxybenzoic acids. The cocrystallization abilities of SMD and EMD with aromatic carboxylic acids were found to be unexpectedly divers despite high formal similarities of these two benzamides and ability of the R2,2(8) heterosynthon formation. The source of diversities of the cocrystallization landscapes is the difference in the stabilization of possible conformers by adopting alternative intramolecular hydrogen boding patterns. The stronger intramolecular hydrogen bonding the weaker affinity toward intermolecular complexation potential. The substituent effects on R2,2(8) heterosynthon properties are also discussed.
On the origin of surfaces-dependent growth of benzoic acid crystal inferred t...Maciej Przybyłek
Crystal growth behavior of benzoic acid crystals on different surfaces was examined. The performed experiments documented the existence of very strong influence introduced by polar surfaces as glass, gelatin, and polyvinyl alcohol (PVA) on the growth of benzoic acid crystals. These surfaces impose strong orientation effect resulting in a dramatic reduction of number of faces seen with x-ray powder diffractions (XPRD). However, scrapping the crystal off the surface leads to a morphology that is similar to the one observed for bulk crystallization. The surfaces of low wettability (paraffin) seem to be useful for preparation of amorphous powders, even for well-crystallizable compounds. The performed quantum chemistry computations characterized energetic contributions to stabilization of morphology related faces. It has been demonstrated, that the dominant face (002) of benzoic acid crystal, growing on polar surfaces, is characterized by the highest densities of intermolecular interaction energies determining the highest cohesive properties among all studied faces. Additionally, the inter-layer interactions, which stand for adhesive properties, are also the strongest in the case of this face. Thus, quantum chemistry computations providing detailed description of energetic contributions can be successfully used for clarification of adhesive and cohesive nature of benzoic acids crystal faces.
On the origin of surface imposed anisotropic growth of salicylic and acetylsa...Maciej Przybyłek
In this paper droplet evaporative crystallization of salicylic acid (SA) and acetylsalicylic acid (ASA) crystals on different surfaces, such as glass, polyvinyl alcohol (PVA), and paraffin was studied. The obtained crystals were analyzed using powder X-ray diffraction (PXRD) technique. In order to better understand the effect of the surface on evaporative crystallization, crystals deposited on glass were scraped off. Moreover, evaporative crystallization of a large volume of solution was performed. As we found, paraffin which is non-polar surface promotes formation of crystals morphologically similar to those obtained via bulk evaporative crystallization. On the other hand, when crystallization is carried out on the polar surfaces (glass and PVA), there is a significant orientation effect. This phenomenon is manifested by the reduction of the number of peaks in PXRD spectrum recorded for deposited on the surface crystals. Noteworthy, reduction of PXRD signals is not observed for powder samples obtained after scraping crystals off the glass. In order to explain the mechanism of carboxylic crystals growth on the polar surfaces, quantum-chemical computations were performed. It has been found that crystal faces of the strongest orientation effect can be characterized by the highest surface densities of intermolecular interactions energy (IIE). In case of SA and ASA crystals formed on the polar surfaces the most dominant faces are characterized by the highest adhesive and cohesive properties. This suggests that the selection rules of the orientation effect comes directly from surface IIE densities.
Formation of chlorinated breakdown products during degradation of sunscreen a...Maciej Przybyłek
In this study, a new degradation path of sunscreen active ingredient, 2-ethylhexyl-4-methoxycinnamate (EHMC) and 4-methoxycinnamic acid (MCA) in the presence of sodium hypochlorite (NaOCl), was discussed. The reaction products were detected using gas chromatography-mass spectrometry (GC-MS). Since HOCl treatment leads to more polar products than EHMC, application of polar extracting agents, dichloromethane and ethyl acetate/n-hexane mixture, gave better results in terms of chlorinated breakdown products identification than n-hexane. Reaction of EHMC with HOCl lead to the formation of C=C bridge cleavage products such as 2-ethylhexyl chloroacetate, 1-chloro-4-methoxybenzene, 1,3-dichloro-2-methoxybenzene, and 3-chloro-4-methoxybenzaldehyde. High reactivity of C=C bond attached to benzene ring is also characteristic for MCA, since it can be converted in the presence of HOCl to 2,4-dichlorophenole, 2,6-dichloro-1,4-benzoquinone, 1,3-dichloro-2-methoxybenzene, 1,2,4-trichloro-3-methoxybenzene, 2,4,6-trichlorophenole, and 3,5-dichloro-2-hydroxyacetophenone. Surprisingly, in case of EHMC/HOCl/UV, much less breakdown products were formed compared to non-UV radiation treatment. In order to describe the nature of EHMC and MCA degradation, local reactivity analysis based on the density functional theory (DFT) was performed. Fukui function values showed that electrophilic attack of HOCl to the C=C bridge in EHMC and MCA is highly favorable (even more preferable than phenyl ring chlorination). This suggests that HOCl electrophilic addition is probably the initial step of EHMC degradation.
Exploring the cocrystallization potential of urea and benzamideMaciej Przybyłek
The cocrystallization landscape of benzamide and urea interacting with aliphatic and aromatic carboxylic acids was studied both experimentally and theoretically. Ten new cocrystals of benzamide were synthesized using an oriented samples approach via a fast dropped evaporation technique. Information about types of known bi-component cocrystals augmented with knowledge of simple binary eutectic mixtures was used for the analysis of virtual screening efficiency among 514 potential pairs involving aromatic carboxylic acids interacting with urea or benzamide. Quantification of intermolecular interaction was achieved by estimating the excess thermodynamic functions of binary liquid mixtures under supercooled conditions within a COSMO-RS framework. The smoothed histograms suggest that slightly more potential pairs of benzamide are characterized in the attractive region compared to urea. Finally, it is emphasized that prediction of cocrystals of urea is fairly direct, while it remains ambiguous for benzamide paired with carboxylic acids. The two known simple eutectics of urea are found within the first two quartiles defined by excess thermodynamic functions, and all known cocrystals are outside of this range belonging to the third or fourth quartile. On the contrary, such a simple separation of positive and negative cases of benzamide miscibility in the solid state is not observed. The difference in properties between urea and benzamide R2,2(8) heterosynthons is also documented by alterations of substituent effects. Intermolecular interactions of urea with para substituted benzoic acid analogues are stronger compared to those of benzamide. Also, the amount of charge transfer from amide to aromatic carboxylic acid and vice versa is more pronounced for urea. However, in both cases, the greater the electron withdrawing character of the substituent, the higher the binding energy, and the stronger the supermolecule polarization via the charge transfer mechanism.
Experimental and theoretical studies on the photodegradation of 2-ethylhexyl ...Maciej Przybyłek
2-Ethylhexyl 4-methoxycinnamate (EHMC) is one of the most commonly used sunscreen ingredient. In this study we investigated photodegradation of EHMC in the presence of such common oxidizing and chlorinating systems as H2O2, H2O2/HCl, H2O2/UV, and H2O2/HCl/UV. Reaction products were detected by gas chromatography with a mass spectrometric detector (GC-MS). As a result of experimental studies chloro-substituted 4-methoxycinnamic acid (4-MCA), 4-methoxybenzaldehyde (4-MBA) and 4-methoxyphenol (4-MP) were identified. Experimental studies were enriched with DFT and MP2 calculations. We found that reactions of 4-MCA, 4-MBA and 4-MP with Cl2 and HOCl were in all cases thermodynamically favorable. However, reactivity indices provide a better explanation of the formation of particular chloroorganic compounds. Generally, those isomeric forms of mono- and dichlorinated compounds which exhibits the highest hardness were identified. Nucleophilicity of the chloroorganic compounds precursors were examined by means of the Fukui function.
Color prediction from first principle quantum chemistry computations: a case ...Maciej Przybyłek
The electronic spectrum of alizarin (AZ) in methanol solution was measured and used as reference data for color prediction. The visible part of the spectrum was modelled by different DFT functionals within the TD-DFT framework. The results of a broad range of functionals applied for theoretical spectrum prediction were compared against experimental data by a direct color comparison. The tristimulus model of color expressed in terms of CIE XYZ and CIE Lab parameters was applied both to experimental and predicted spectra. It was found that the HSE03 method along with the 6-31G(d,p) basis set provides the most accurate color prediction, much better than other commonly used functionals such as B3LYP, CAM-B3LYP or PBE0. Besides, the influence of potential errors, introduced by theoretical predictions on color estimation, was examined for different wavelengths. The obtained results showed that color prediction is significantly dependent on the type of basis set and functional applied. The proposed methodology provides a simple, straightforward and more reliable way of theoretical protocols validation than just a comparison of experimental and estimated values of maximum absorbance wavelength.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Nucleophilic Addition of carbonyl compounds.pptxSSR02
Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
Carbonyls undergo addition reactions with a large range of nucleophiles.
Comparing the relative basicity of the nucleophile and the product is extremely helpful in determining how reversible the addition reaction is. Reactions with Grignards and hydrides are irreversible. Reactions with weak bases like halides and carboxylates generally don’t happen.
Electronic effects (inductive effects, electron donation) have a large impact on reactivity.
Large groups adjacent to the carbonyl will slow the rate of reaction.
Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
2. Molecules 2022, 27, 5274 2 of 16
cells [12], fluorescent probes [13], sensitizers [14], laser dyes [15], and inhibitor additives to
different materials [16]. Even more importantly, coumarin and its derivatives have some
beneficial biological activities, including antioxidant [17], anticoagulant [18], antibacte-
rial [19], anti-inflammatory [20], antiviral [21], and enzyme inhibitory [22] actions, which
make them widely used in medicine [23].
Considering coumarin manufacturing, solvent selection plays a crucial role. Aliphatic
alcohols, especially biobased ones such as ethanol, glycerol, and 2-propanol, are considered
to be efficient and relatively green extracting agents for nutraceuticals [24,25]. For instance,
according to Bourgaud et al. [26], proton-donating and polar solvents, such as water,
ethanol, and methanol, were more efficient for the extraction of coumarin from Melilotus
officinalis L. than chloroform, diethyl ether, and ethyl acetate. This is understandable since
coumarin and its derivatives are, in general, highly proton-accepting molecules [27–29].
Furthermore, the aqueous solubility of coumarin decreases with the increase of pH [30],
which confirms its relatively basic character.
The nature of solute and solvent, determining their mutual affinity, and the ther-
modynamic parameters related to the stability of the crystal lattice, are the key factors
affecting solubility. Among a variety of theoretical models developed to describe the
solubility–temperature relationships, the in silico quantum-chemical computations are the
most intriguing since they are based on the information retrieved from the 3D molecu-
lar structure. In principle, they provide actual solubility predictions [31], in contrast to
many models offering merely back-computations, such as, for example, the van’t Hoff [32],
Apelblat [33,34], Buchowski-Ksiazczak (λh) [35], Wilson [36], NRTL [37], and Jouyban-
Acree [38] models. One of the most recognized in silico approaches is the conductor-like
screening model for real solvents, COSMO-RS [39–42]. It deserves special attention due
to its efficiency, universality, and clear thermodynamic interpretation and for following
chemical intuition.
The aim of this paper is fourfold. First of all, the theoretical protocol for resolving
inconsistencies in reported solubility data is formulated. Second, a validation of this
theoretical approach is performed by experimental remeasurements of already published
solubility data. Third, for providing a broader perspective, a series of structurally similar
solvents are used for additional confirmation of the theoretically drawn conclusions about
the coherency of the solubility dataset by including newly measured cases. Finally, an
interpretation of the COSMO-RS-DARE parameters is offered by correlating the computed
values with popular molecular descriptors.
2. Materials and Methods
2.1. Materials
Coumarin (CAS: 91-64-5, MW = 143.14 g/mol) was purchased from Sigma Aldrich
(Saint Louis, MO, USA), and the purity of this chemical was ≥99% according to the supplier.
All of the solvents used were also provided by Sigma Aldrich and included: methanol
(CAS: 67-56-1, MW = 32.04), ethanol (CAS: 64-17-5, MW = 46.07 g/mol), 1-propanol (CAS:
71-23-8, MW = 60.10 g/mol), 2-propanol (CAS: 67-63-0, MW = 60.10 g/mol), 1-butanol
(CAS: 71-36-13, MW = 74.12), 1-pentanol (CAS: 71-41-0, MW = 88.15 g/mol), and 1-octanol
(CAS: 111-87-5, MW = 130.23 g/mol). The purity of all solvents was ≥99%.
2.2. Calibration Curve
The calibration curve used for the determination of coumarin solubility was pre-
pared with the use of a stock solution of coumarin in methanol with a concentration
of 0.0333 mg/mL. This solution was then successfully diluted by transferring its fixed
amounts to 10 mL volumetric flasks and adding methanol. The obtained series of solutions
with decreasing coumarin concentrations was measured spectrophotometrically, and the
absorbance values found at 310 nm wavelength were plotted against the corresponding
concentration values. Three separate curves were prepared and then averaged, with the
resulting linear equation being y = 42.346x + 0.0085. The curve can be characterized by
3. Molecules 2022, 27, 5274 3 of 16
high linearity, with the determination coefficient of R2 = 0.9997. The limit of detection
(LOD) and limit of quantification (LOQ) were found to be LOD = 4.93 × 10−4 mg/mL and
LOQ = 1.48 × 10−3 mg/mL, which were well below the coumarin concentrations found in
the samples.
2.3. Sample Preparation
In this study, the shake-flask-type method of solubility determination was used. As
documented in previous studies [43–48], the applied procedure was found to be useful
and reliable in the case of various pharmaceutically active compounds. The samples used
for solubility measurements were prepared by adding an excess amount of coumarin to
10 mL volumetric flasks that were then filled with the appropriate solvent in order to
obtain saturated solutions. The prepared samples were incubated for 24 h at four different
temperatures (25–40 ◦C with 5 ◦C intervals) using an ES-20/60 Orbital Shaker Incubator
supplied by Biosan (Riga, Latvia). The temperature adjustment accuracy was 0.1 ◦C, and
its variance during the daily cycle was ±0.5 ◦C. Moreover, the mixing of the samples at
60 rev/min was provided by the incubator. In the next step, the samples were filtered
using a syringe with a PTFE filter with a 22 µm pore size. All of the test tubes, syringes,
and filters were preheated to the appropriate temperature to avoid the precipitation of
dissolved coumarin. Finally, fixed amounts of the filtrate were transferred to test tubes,
which were prefilled with a set amount of methanol, and samples prepared in this way
were measured spectrophotometrically.
2.4. Solubility Measurements
The concentration of coumarin in the samples was determined through spectrophoto-
metric measurements using an A360 spectrophotometer from AOE Instruments (Shanghai,
China). Spectra in the 190–700 nm wavelength range were recorded with a 1 nm resolu-
tion, and samples were diluted with methanol, which was also used as a reference. The
absorbance values at 310 nm were used in conjunction with the calibration curve prepared
earlier. Three samples were measured for each data point, and their concentrations were
averaged and expressed as mole fractions.
2.5. COSMO-RS-DARE Computations
COSMO-RS-DARE (dimerization, aggregation, and reaction extension) [49] is an
adaptation of the COSMO-RS approach [39–41] for treating bulk systems by including
concentration-dependent composition alterations imposed by diverse reactions in the bulk
system. The adaptation of this approach for solids solubility computations was detailed
in our previous papers dealing with neat solvents [50], binary mixtures [45], and ternary
systems [51]. Therefore, only brief remarks are provided here. In this study, both COSMO-
RS and COSMO-RS-DARE computations were carried out using COSMOtherm (version
22.0.0, Dassault Systèmes, Biovia: San Diego, CA, USA) [52] software. The most important
difference between these approaches is the definition of conformers included in the thermo-
dynamic property computations. In both methods, each component is represented by the
set of the most representative conformers, which are identified during the initial phase prior
to the actual thermodynamic property computations. Typically, the conformational analysis
leads to a set of low-energy structures of every component of the considered bulk system.
For this purpose, the COSMOconf program [53] can be used to offer an automatization of
this process. However, such a procedure is unable to identify multicomponent clusters that
might potentially occur in the system due to direct interactions between components. These
complexes can significantly differ in their electron density properties, which are essential
for the COSMO-RS approach. Hence, the pool of conformers of monomers is extended,
with the ones identified in the separate conformational analysis including bimolecular con-
tacts. After generating potentially important pairs, the full clustering algorithm is applied
to reduce the number of conformers and eliminate very similar clusters or those of low
probability due to the energy values exceeding the selected threshold with respect to the
4. Molecules 2022, 27, 5274 4 of 16
most favorable one. All the results presented here were computed using the TURBOMOLE
program [54,55] with in-house-developed scripts. There is one important modification im-
plemented in this paper due to problems encountered during the optimization of coumarin
dimers in the case of applying the RI-DFT BP86 (B88-VWN-P86) functional along with
the def-TZVP basis set. For consistency with parametrization sets of COSMOtherm, the
geometries optimized in such a manner are used for the final generation of “cosmo” and
“energy” files by single-point energy computations in an extended def2-TZVPD basis set
using the same functional. Unfortunately, optimization trials of coumarin pairs failed using
this approach since coumarin, as an aprotic compound, cannot form dimers stabilized by
hydrogen bonds. Pairs of this type were identified in the case of heteromolecular contacts
with proton-donating molecules such as alcohols or water. However, the expected stacked
dimers of coumarin were not obtained since monomers tend to separate from each other
while using this type of geometry optimization. The reason for this was the inappropriate
accounting of contributions coming from electron dispersion and non-covalent interactions.
Hence, geometry optimization was performed using an alternative approach. Since the
basis superposition error (BSSE) can be an important contribution to pairs stabilization
energy, the geometry optimizations were performed in consistency with geometry-based
counterpoise corrections (gCP) [56] of the pairs stabilization energies. This parametrization
relies on the BP97 GGA functional used with the def2-SVPD basis set and Grimme D3-BJ
dispersion corrections [57]. Fortunately, this level of geometry optimization led to stable
coumarin pairs in stacked conformations, which is not surprising since this meta-GGA
functional is commonly accepted as a reliable one for intermolecular interaction character-
istics [58]. Hence, the obtained geometries of pairs were used for the preparation of the
final input files, which were necessary for the utilization of the BP_TZVPD_FINE_22.ctd
parametrization in COSMOtherm by completing the single-point energy computations on
the required RI-DFT BP86/def2-TZVPD level.
For every system, the COSMO-RS-DARE approach introduces two fitting parameters
defining intermolecular interactions between those centers that are not included in the
default COSMO-RS statistical analysis. The mathematical form describing these parameters
resembles the Gibbs free energy equation as follows:
Gint
ij (T) = Hint
ij − T·Sint
ij (1)
where the enthalpic, Hint
ij , and entropic, Sint
ij , contributions of the interactions between the
i-th and j-th species are considered to be temperature-independent. These parameters are
computed by fitting to experimental solubility data. It is important to note that the linear
function defined by Equation (1) holds for many systems with very high accuracy, irrespec-
tive of the number of temperatures used for solubility determination. The intermolecular
interaction thermodynamic parameters defined in Equation (1) can be used for assessments
of enthalpy–entropy compensation by the analogy to a similar analysis conducted with
the aid of a solvation thermodynamic function determined via a van’t Hoff plot. Here, the
following definition is the direct analogy of the enthalpy–entropy compensation factor:
χ =
h
Hint
ij
i
h
Hint
ij
i
+
h
T·Sint
ij
i (2)
The meaning remains the same as in the original formulation and simply quantifies
the contributions of the energetic and entropic terms in the total Gibbs free energy of
interaction. Indeed, the dominance of the energetic component of the interaction in the
system is indicated by values higher than 0.5. In the case of values lower than half, the
entropic contribution overrides the enthalpic one.
5. Molecules 2022, 27, 5274 5 of 16
3. Results and Discussion
The direct impulse for this work was the observed incongruences in the reported
solubility data of coumarin provided by Huang et al. [59,60] (set A) and Akay et al. [61] (set
B). Particular interest was narrowed to the alcohols used as neat solvents. The published
values differ dramatically, especially for elevated temperatures. This problem was already
raised by Akay et al. [61], who honestly provided data comparison. The authors offered
general explanations for the observed inconsistencies, relating them mainly to the accuracy
of the analytical method or solution–solid equilibrium establishment. However, the scien-
tific audience was left with two distinct sets of solubility data. The observed deviations
of the reported values most probably cannot characterize the same physical system, and
some serious methodological issues are at play. Although it is difficult to compare different
datasets due to the different experimental conditions, according to Huang et al. [59,60], the
solution–solid equilibrium in the case of coumarin can be achieved after 8 h, which includes
3 h without agitation for the settling of undissolved particles. In the case of Akay et al. [61],
the sample agitation and incubation time was 18 h. It is noteworthy that in this study the
samples were equilibrated for an even longer period (24 h).
Since solubility data are used for very detailed thermodynamic analysis, conflicting
values lead to completely different system characteristics. It is then of crucial importance
to critically assess the solubility data, especially since they directly affect the validity of
the preferential solvation analysis performed [61] in terms of the inverse Kirkwood–Buff
integrals formalism. The most straightforward way, of course, would be a repetition of the
experiments with the hope that new measurements would resolve the observed conflict,
including eventual recomputations of coumarin-preferential solvation. However, without
avoiding this goal, the motivation of this work is a bit wider, aiming to develop a general
theoretical approach that might be used for testing solubility data consistency. Coumarin
is merely an exemplary case that is used for validation purposes and to direct further
experiments. In our local solubility database, there are many more such cases, and their
identification for data curation might be interesting for a broad scientific audience. In this
context, it is worth citing at this point a precedent that took place in the circumstance of the
critical evaluation of maleic acid solubility [62]. Hence, a theoretical tool suitable for data
consistency analysis seems to be valuable.
3.1. The COSMO-RS-DARE Solubility Computations
There are several first-principle approaches that might be adopted for the purpose
of consistency tests of available solubility data. From our perspective, the method of first
choice is the COSMO-RS framework [39,42], which is often applied for characteristics of
bulk systems using only information about molecular structure. Unfortunately, solubility
computations using this method suffer, in many cases, from serious inaccuracies [44,45,50],
although some systems can be characterized with quite satisfactory correctness [43,50].
Previously published reports [44,45,51] suggested that one possible way is to enhance the
default COSMO-RS computation with the inclusion of information about intermolecu-
lar interactions occurring in the saturated systems by providing the structures of binary
clusters. This is carried out via the COSMO-RS-DARE framework, formulated as an exten-
sion of COSMO-RS for modeling systems showing concentration-dependent alterations
of qualitative and quantitative compositions. As mentioned in the Methods Section, this
approach offers very high accuracy at a cost of two fitting parameters for every system.
However, these parameters have a deeper meaning, and the origin of their introduction
is also quite clear. Indeed, the proper definition of a solute–solvent system requires an
adequate representation of solute conformations. This includes not only the monomeric
forms of flexible compounds but also structures altered by direct contacts with the con-
stituents of the bulk system. In the case of neat solvents, two types of such clusters can
play the most important role, namely, solute–solute and solute–solvent interactions. The
third type, which is the solute–solute interaction, is ignored in the case of solubility com-
putations [44,45]. It was already documented [63] that the restriction to include just pairs
6. Molecules 2022, 27, 5274 6 of 16
is quite sufficient for a proper representation of intermolecular clusters in the solubility
computations. The same approach is applied here for the determination of values of these
two fitting parameters defined by Equation (1). The obtained values characterizing set
A and set B are collected in Table 1. In addition, in Figure 1, the temperature trends of
corresponding Gint values are plotted for these systems. First of all, it is worth emphasizing
that, according to expectations, a high linearity of all plots is observed. This is a fortunate
circumstance justifying the computation of only two parameters per system. Furthermore,
one can see that discrepancies in the solubility values between the two considered sets of
data seriously affect the intermolecular interaction parameter, Gint(T). There are observed
opposite trends of all black and gray lines, suggesting reverse temperature trends. The
interactions in set A decrease with the rise of temperature, whereas for set B an opposite
conclusion is drawn. This is associated with the discrepancies in the obtained Hint and Sint
data, as provided in Table 1. In the case of water and ethanol, the values of Hint are positive
for set B, contrary to the values obtained for set A. A similar change in the sign is observed
for the entropic contribution, Sint.
Table 1. Results of COSMO-RS-DARE computations characterizing coumarin solubility in neat
methanol (MeOH), ethanol (EtOH), 1-propanol (1PrOH), 2-propanol (2PrOH), 1-butanol (1BuOH),
1-pentanol (1PeOH), 1-octanol (1OcOH), and water (W). Three analyzed datasets are denoted as
(A) [59,60], (B) [61], and (C)–this work. The last column comprises the values of the enthalpy–entropy
compensation factor computed according to Equation (2).
Solvents
Hint
[kcal/mol]
Sint
[cal/mol/K)
R2 χ
MeOH (A) −23.09 69.80 0.996 0.64
EtOH (A) −24.91 72.07 0.997 0.66
1PrOH (A) −26.14 74.82 0.999 0.67
2PrOH (A) −29.32 84.01 0.997 0.69
W (A) −17.30 46.73 0.995 0.57
EtOH (B) 7.02 −33.77 1.000 0.35
W (B) 5.48 −24.99 0.967 0.29
MeOH (C) −22.77 68.54 0.994 0.63
EtOH (C) −26.17 76.03 0.984 0.67
1PrOH (C) −26.87 76.80 0.986 0.67
2PrOH (C) −31.22 89.90 0.980 0.70
1BuOH (C) −32.44 91.39 0.980 0.71
1PeOH (C) −40.38 117.41 0.988 0.75
1OcOH (C) −38.76 111.22 0.993 0.75
Molecules 2022, 27, x FOR PEER REVIEW 7 of 17
Figure 1. Temperature trends of COSMO-RS-DARE interaction parameter, Gint(T), characterizing
coumarin solubility in neat alcohols and water. Black solid lines represent set A [59,60], grey solid
lines correspond to set B [61], and red dotted lines characterize data measured in this work (set C).
In conclusion to this part, it is worth emphasizing that the application of COSMO-
RS-DARE for the determination of interaction parameters clearly distinguishes set A from
set B. Although there seems to be an internal consistency within each of these sets, the
comparison of solubility with data measured by Huang et al. [59,60] in structurally similar
solvents suggests the consistency of set A with the general trends of the computed values
Figure 1. Temperature trends of COSMO-RS-DARE interaction parameter, Gint(T), characterizing
coumarin solubility in neat alcohols and water. Black solid lines represent set a [59,60], grey solid
lines correspond to set b [61], and red dotted lines characterize data measured in this work (set c).
7. Molecules 2022, 27, 5274 7 of 16
In conclusion to this part, it is worth emphasizing that the application of COSMO-RS-
DARE for the determination of interaction parameters clearly distinguishes set A from set B.
Although there seems to be an internal consistency within each of these sets, the comparison
of solubility with data measured by Huang et al. [59,60] in structurally similar solvents
suggests the consistency of set A with the general trends of the computed values of Gint(T).
Hence, based on this observation, one should cautiously accept that set A more reliably
characterizes coumarin solubility in selected alcohols. To further support this conclusion, it
is worth inspecting the accuracy of the performed first-principle solubility computations.
The correlation between the estimated and experimental values is presented in Figure 2 and
suggests that the COMSO-RS-DARE predictions are very accurate, in contrast to the default
COSMO-RS predictions. Hence, the high reliability of the COSMO-RS-DARE computations
of solubility in neat solvents supports the application of this approach for the inspection of
dataset consistency.
Figure 1. Temperature trends of COSMO-RS-DARE interaction parameter, Gint(T), characterizing
coumarin solubility in neat alcohols and water. Black solid lines represent set A [59,60], grey solid
lines correspond to set B [61], and red dotted lines characterize data measured in this work (set C).
In conclusion to this part, it is worth emphasizing that the application of COSMO-
RS-DARE for the determination of interaction parameters clearly distinguishes set A from
set B. Although there seems to be an internal consistency within each of these sets, the
comparison of solubility with data measured by Huang et al. [59,60] in structurally similar
solvents suggests the consistency of set A with the general trends of the computed values
of Gint(T). Hence, based on this observation, one should cautiously accept that set A more
reliably characterizes coumarin solubility in selected alcohols. To further support this con-
clusion, it is worth inspecting the accuracy of the performed first-principle solubility com-
putations. The correlation between the estimated and experimental values is presented in
Figure 2 and suggests that the COMSO-RS-DARE predictions are very accurate, in con-
trast to the default COSMO-RS predictions. Hence, the high reliability of the COSMO-RS-
DARE computations of solubility in neat solvents supports the application of this ap-
proach for the inspection of dataset consistency.
Figure 2. Correlation between estimated and experimental solubility of coumarin in neat alcohols
and pure water.
Figure 2. Correlation between estimated and experimental solubility of coumarin in neat alcohols
and pure water.
3.2. The Experimental Validation of Theoretical Consistency Test
The final approval of the considered method must always come from experiments.
Hence, the validity of the consistency test of coumarin solubility data performed in the
theoretical manner was inspected by performing a sequence of new experiments for a series
of seven alcohols. Four were used to directly reproduce the solvents belonging to set A,
and in addition, three new solvents were included to extend the set of structurally similar
solvents. The obtained values are plotted in Figure 3, and numerical data are collected
in the Supplementary Materials (Table S1). In the left panel of Figure 3, the results of the
mole fraction solubility of coumarin in neat alcohols, except for ethanol, are collected. The
coumarin solubility in this solvent is plotted in the right panel of Figure 3, along with the
one belonging to set B [61]. The presented results clearly confirm the observations made
due to the performed COSMO-RS-DARE analysis. The results of our measurements of
coumarin solubility in ethanol are almost identical to those included in set A, with very
similar temperature solubility trends. Although the results of our measurements tend to
be slightly lower for the more elevated temperatures compared to the data provided by
Huang et al. [59,60], the error is within a few percent. The same conclusion can be drawn
from the analysis of the rest of considered systems.
8. Molecules 2022, 27, 5274 8 of 16
in the Supplementary Materials (Table S1). In the left panel of Figure 3, the results of the
mole fraction solubility of coumarin in neat alcohols, except for ethanol, are collected. The
coumarin solubility in this solvent is plotted in the right panel of Figure 3, along with the
one belonging to set B [61]. The presented results clearly confirm the observations made
due to the performed COSMO-RS-DARE analysis. The results of our measurements of
coumarin solubility in ethanol are almost identical to those included in set A, with very
similar temperature solubility trends. Although the results of our measurements tend to
be slightly lower for the more elevated temperatures compared to the data provided by
Huang et al. [59,60], the error is within a few percent. The same conclusion can be drawn
from the analysis of the rest of considered systems.
Figure 3. Solubility values of coumarin measured in pure alcohols. The notation is consistent with
the one used in Figure 1.
The COSMO-RS-DARE was also applied for the interpretation of the new solubility
data reported in this work, and the resulting intermolecular parameters are collected in
Figure 1 and Table 1, documenting a coherent pattern of our measurements and those
included in set A [59,60]. However, the mentioned slight deviation between these two sets
at higher temperatures also results in slightly lower values of Hint and Sint, as documented
in Table 1.
For the final test of the consistency of the coumarin solubility data, the values of the
enthalpy–entropy compensation factor, χ, were determined for all considered series. In
the solubility literature, this parameter is used in the context of apparent solvation en-
thalpy and entropy determined using the van’t Hoff model. Here, formally, the same for-
mula is applied, but the thermodynamic values are represented by interaction parameters
determined using COSMO-RS-DARE. Hence, the values collected in Table 1 and plotted
in Figure 4 were computed using Equation (2) for T = 298.15 K. A modest linear trend of
χ in relation to the number of carbon atoms in the solvent molecules of neat alcohols is
observed. This allows for at least qualitative characteristics and is supposed to be suffi-
cient for the identification of outliers. Indeed, the values of χ computed for sets A and C
suggest that the energetic contribution has a dominant effect on the total Gibbs free energy
of interaction, and the entropic term computed for room temperature reaches roughly one
Figure 3. Solubility values of coumarin measured in pure alcohols. The notation is consistent with
the one used in Figure 1.
The COSMO-RS-DARE was also applied for the interpretation of the new solubility
data reported in this work, and the resulting intermolecular parameters are collected in
Figure 1 and Table 1, documenting a coherent pattern of our measurements and those
included in set A [59,60]. However, the mentioned slight deviation between these two sets
at higher temperatures also results in slightly lower values of Hint and Sint, as documented
in Table 1.
For the final test of the consistency of the coumarin solubility data, the values of the
enthalpy–entropy compensation factor, χ, were determined for all considered series. In the
solubility literature, this parameter is used in the context of apparent solvation enthalpy and
entropy determined using the van’t Hoff model. Here, formally, the same formula is applied,
but the thermodynamic values are represented by interaction parameters determined using
COSMO-RS-DARE. Hence, the values collected in Table 1 and plotted in Figure 4 were
computed using Equation (2) for T = 298.15 K. A modest linear trend of χ in relation to the
number of carbon atoms in the solvent molecules of neat alcohols is observed. This allows
for at least qualitative characteristics and is supposed to be sufficient for the identification
of outliers. Indeed, the values of χ computed for sets A and C suggest that the energetic
contribution has a dominant effect on the total Gibbs free energy of interaction, and the
entropic term computed for room temperature reaches roughly one third of the interaction
energetics. Conclusions drawn from the data of set B are exactly the opposite, suggesting
stronger contributions of the entropic term, which seems to be unlikely.
Molecules 2022, 27, x FOR PEER REVIEW 9 of 17
third of the interaction energetics. Conclusions drawn from the data of set B are exactly
the opposite, suggesting stronger contributions of the entropic term, which seems to be
unlikely.
Figure 4. The correlation between the enthalpy–entropy compensation factor and the number of
carbon atoms in alcohol molecules computed for room temperature.
3.3. COSMO-RS-DARE Parameters Interpretation
Although this paper was prepared with a very simple and practical aim, which is
solubility data curation, the application of COSMO-RS-DARE offers many interesting de-
tails regarding the mechanism of solubility. Hence, some additional information is pro-
vided here for the enhancement of the solubility interpretation of coumarin in neat alco-
hols. Using this sophisticated methodology requires prior generation, optimization, and
clustering of pairs formed between the solute and solvent molecules. The most stable clus-
ters are collected in Figure 5, along with energetic and geometric characteristics.
It is interesting to note that based on the data provided in Figure 5 it can be concluded
Figure 4. The correlation between the enthalpy–entropy compensation factor and the number of
carbon atoms in alcohol molecules computed for room temperature.
9. Molecules 2022, 27, 5274 9 of 16
3.3. COSMO-RS-DARE Parameters Interpretation
Although this paper was prepared with a very simple and practical aim, which is
solubility data curation, the application of COSMO-RS-DARE offers many interesting
details regarding the mechanism of solubility. Hence, some additional information is
provided here for the enhancement of the solubility interpretation of coumarin in neat
alcohols. Using this sophisticated methodology requires prior generation, optimization,
and clustering of pairs formed between the solute and solvent molecules. The most stable
clusters are collected in Figure 5, along with energetic and geometric characteristics.
Molecules 2022, 27, x FOR PEER REVIEW 10 of 17
Figure 5. Characteristics of selected energetic and geometric properties of the most stable pairs of
coumarin with constituents of the studied systems.
Figure 5. Characteristics of selected energetic and geometric properties of the most stable pairs of
coumarin with constituents of the studied systems.
10. Molecules 2022, 27, 5274 10 of 16
It is interesting to note that based on the data provided in Figure 5 it can be concluded
that the elongation of the aliphatic chain affects the mutual orientation of the interacting
alcohol molecules with respect to coumarin, but it only slightly alters the geometry of the
hydrogen bond. The more carbon atoms in the alcohol molecule, the stronger the contri-
bution of dispersion interactions and the overlapping of interacting molecules. Indeed,
methanol is exposed outside and is placed in the plane with respect to coumarin. Starting
from butanol, the alcohol molecules were placed above the plane of coumarin, enabling
interactions of aliphatic chains with coumarin rings. Coumarin is highly aromatic, which
is granted by the six-carbon ring. Hence, long enough chains are strongly attracted by
delocalized electrons, which is responsible for strengthening the stability of intermolecular
interactions, as documented by the values of the Gibbs free energy of reaction, leading to
given pairs in the given solution at room temperature.
The application of COSMO-RS-DARE has one serious disadvantage, which is the
necessity to introduce two fitting parameters accounting for interactions between new
pseudo-conformers constituting solute–solvent complexes. The first question is whether
these new species are different from monomeric conformers. The answer to this question
is provided in Figure 6, which collects σ-profiles computed for the coumarin monomer
and molecules involved in pair formation. The σ-profiles, which have a simple meaning of
histograms collecting distributions of charge density, are in line with chemical intuition. As
depicted in Figure 6, three regions can be distinguished, characterizing hydrogen bond-
ing properties and hydrophobicity. The comparison of the plots provided for coumarin
monomer, dimer, and pairs with methanol or octanol suggests that intermolecular interac-
tions seriously affect charge density distributions.
, 27, x FOR PEER REVIEW 11 of 17
The application of COSMO-RS-DARE has one serious disadvantage, which is the ne-
cessity to introduce two fitting parameters accounting for interactions between new
pseudo-conformers constituting solute–solvent complexes. The first question is whether
these new species are different from monomeric conformers. The answer to this question
is provided in Figure 6, which collects σ-profiles computed for the coumarin monomer
and molecules involved in pair formation. The σ-profiles, which have a simple meaning
of histograms collecting distributions of charge density, are in line with chemical intuition.
As depicted in Figure 6, three regions can be distinguished, characterizing hydrogen
bonding properties and hydrophobicity. The comparison of the plots provided for cou-
marin monomer, dimer, and pairs with methanol or octanol suggests that intermolecular
interactions seriously affect charge density distributions.
Figure 6. Exemplary σ-profile plots characterizing the coumarin monomer not involved in direct
contacts, the dimer in stacked conformation, and hydrogen-bonded heteromolecular pairs with
methanol and 1-octanol. The hydrophobicity region was defined as the charge density range be-
tween −0.08 and +0.08 e·
Å −2.
According to expectations, the HB donicity of coumarin is negligible irrespective of
the form (monomeric or dimeric). A slightly higher HB acceptability of coumarin is ex-
pected due to the presence of electronegative centers. However, the strong aromaticity of
coumarin is associated with its high hydrophobic character. It is interesting to note that
Figure 6. Exemplary σ-profile plots characterizing the coumarin monomer not involved in direct
contacts, the dimer in stacked conformation, and hydrogen-bonded heteromolecular pairs with
methanol and 1-octanol. The hydrophobicity region was defined as the charge density range between
−0.08 and +0.08 e·Å−2.
11. Molecules 2022, 27, 5274 11 of 16
According to expectations, the HB donicity of coumarin is negligible irrespective
of the form (monomeric or dimeric). A slightly higher HB acceptability of coumarin is
expected due to the presence of electronegative centers. However, the strong aromaticity
of coumarin is associated with its high hydrophobic character. It is interesting to note
that hydrophobic interactions are seriously affected by the intermolecular interactions
of coumarin. Indeed, dimers adopting stacked conformations are significantly less hy-
drophobic compared to the free monomer. Moreover, the interactions with long-chain
alcohols reduce the hydrophobicity of such coumarin conformers due to the abovemen-
tioned structure of such heteromolecular complexes. On the contrary, interactions with
methanol increase the hydrophobicity of coumarin due to the induction effect being the
consequence of hydrogen bond formation. Furthermore, there is also a visible influence of
the hydrogen bond formation on the HB acceptability of coumarin involved in pairs. It is
quite understandable that interaction with methanol depletes its acceptability for further
hydrogen bonding. On the other hand, dimers are as much prone to HB formation as
monomers. There is also an interesting trend of HB donicity with affinities of coumarin to
alcohols. The higher the ∆Gr (lower affinity), the stronger the alteration of HB acceptability.
Hence, conclusions drawn from the exemplary σ-profiles provided in Figure 6 emphasize
the necessity of including new species of coumarin in the description of saturated solutions
in alcohols, and omitting them is one of the sources of the failed solubility computations of
the default COSMO-RS approach.
However, a problem remains with the parameters introduced by COSMO-RS-DARE,
the values of which are to be derived based on experimental data. It is reasonable to expect
that some external characteristics might help in estimating the values of these interaction
parameters. One such example was already provided in the case of ethenzamide [50], for
which a linear relationship was found between the COSMO-RS-DARE parameters and
pairs affinity. The general problem with finding relationships of this type is the interplay
of the shortcomings of the COSMO-RS model and the improper systems definition in the
solubility computations. For chemically different solutes dissolved in solvents of different
physicochemical properties, these two contributions are not equal, making it harder to find
molecular descriptors suitable for accounting for the values of Gint.
However, the situation is not as hopeless as it might seem. Here, a structurally similar
set of solvents is studied with the same solute. In such a restricted chemical space, finding
appropriate molecular descriptors for Gint computation seems to be feasible. To demon-
strate this possibility, several descriptors were computed using the PaDEL software [64] and
related to the interaction parameters resulting from the COSMO-RS-DARE computations.
Additionally, the Hansen solubility parameters (HSP) expressing dispersion (δd), dipolar
(δp), and hydrogen-bonding forces (δHB) were retrieved from Hansen Solubility Parameters:
A User’s Handbook [65] and used for the determination of the solubility space distance (Ra)
values between coumarin and alcohols (Equation (3)).
Ra =
r
4
δsolute
d − δsolvent
d
2
+
δsolute
p − δsolvent
p
2
+
δsolute
HB − δsolvent
HB
2
(3)
Although the HSP concept is very popular in polymer studies, it has also been widely
applied for describing the solubility behavior of low-molecular-weight compounds in
popular neat and multicomponent organic solvents, including aliphatic alcohols [66–71].
It is noteworthy that HSP were also applied in the case of coumarin for describing the
solubilizing effects of choline-based natural deep eutectic solvents [72]. Therefore, HSP and
Ra were included in the set of descriptors considered in this study.
Since Gint is temperature-dependent and the above molecular descriptors are not, the
linear regressions were defined separately for each temperature used in our measurements.
In Figure 7, the regression plots for room temperature are exemplified.
12. Molecules 2022, 27, 5274 12 of 16
FOR PEER REVIEW 13 of 17
Figure 7. Exemplary regressions documenting the quality of the linear relationships between the
COSMO-RS-DARE interaction parameter, Gint, and molecular descriptors SpMin2_Bhm (Burden
modified eigenvalue descriptor) and Ra (distance between solute and solvent in the Hansen solu-
bility space).
Among many molecular descriptors computable in PaDEL, the Burden modified ei-
genvalue descriptor, SpMin2_Bhm, was found to be linearly correlated with Gint. This is a
relative mass weighted 2D molecular index related to the smallest absolute eigenvalue of
a Burden modified matrix [73–75]. Since, there is a very good correlation between
SpMin2_Bhm and δp (R2 = 0.94) or δHB (R2 = 0.97), the physical meaning of this parameter
is associated with the polarity and hydrogen bond formation abilities of the solvent. As
evidenced in Figure 7, the values of the distance between the solute and solvent in the
Hansen solubility space can also be used as a measure of Gint. This fortunate circumstance
of a linear relationship enables computations of Gint, which might be further used in
COMSO-RS-DARE calculations. The results of such computations are provided in Figure
8, which also includes the results of the default solubility predictions. It is worth mention-
ing that the models are statistically meaningful. The values of the SpMin2_Bhm and Ra
descriptors used for the Gint calculation and the statistical characteristics of the regression
between xest and xexp are provided in the Supplementary Materials (Tables S3 and S4).
y = −0.36x − 0.37
R² = 0.96
y = 1.71x + 22.00
R² = 0.94
0
2
4
6
8
10
12
14
16
18
20
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
–6.0 –5.5 –5.0 –4.5 –4.0 –3.5 –3.0 –2.5 –2.0
R
a
SpMin2_Bhm
Gint [kcal/mol]
Figure 7. Exemplary regressions documenting the quality of the linear relationships between the
COSMO-RS-DARE interaction parameter, Gint, and molecular descriptors SpMin2_Bhm (Burden modified
eigenvalue descriptor) and Ra (distance between solute and solvent in the Hansen solubility space).
Among many molecular descriptors computable in PaDEL, the Burden modified
eigenvalue descriptor, SpMin2_Bhm, was found to be linearly correlated with Gint. This is
a relative mass weighted 2D molecular index related to the smallest absolute eigenvalue
of a Burden modified matrix [73–75]. Since, there is a very good correlation between
SpMin2_Bhm and δp (R2 = 0.94) or δHB (R2 = 0.97), the physical meaning of this parameter
is associated with the polarity and hydrogen bond formation abilities of the solvent. As
evidenced in Figure 7, the values of the distance between the solute and solvent in the
Hansen solubility space can also be used as a measure of Gint. This fortunate circumstance of
a linear relationship enables computations of Gint, which might be further used in COMSO-
RS-DARE calculations. The results of such computations are provided in Figure 8, which
also includes the results of the default solubility predictions. It is worth mentioning that
the models are statistically meaningful. The values of the SpMin2_Bhm and Ra descriptors
used for the Gint calculation and the statistical characteristics of the regression between xest
and xexp are provided in the Supplementary Materials (Tables S2 and S3).
The mean average percentage error of the solubility values computed using Gint
estimated with the aid of the SpMin2_Bhm descriptor was 15.2% (RMSD = 0.021), whereas
the analogical value corresponding to Ra was equal to 14.0% (RMSD = 0.016). This is less
precise compared to the Gint values fully fitted to the experimental data but much higher
if confronted with a 240% mean average percentage error (RMSD = 0.19) for the default
COSMO-RS computations of coumarin solubility.
13. Molecules 2022, 27, 5274 13 of 16
Molecules 2022, 27, x FOR PEER REVIEW 14 of 17
Figure 8. The results of the solubility prediction of coumarin in neat alcohols using the COSMO-RS
and COSMO-RS-DARE approaches. The back-computed solubility values with Gint parameters fully
fitted to experimental data were augmented by the ones resulting from the linear relationships pro-
vided in Figure 7.
The mean average percentage error of the solubility values computed using Gint esti-
mated with the aid of the SpMin2_Bhm descriptor was 15.2% (RMSD = 0.021), whereas
the analogical value corresponding to Ra was equal to 14.0% (RMSD = 0.016). This is less
precise compared to the Gint values fully fitted to the experimental data but much higher
if confronted with a 240% mean average percentage error (RMSD = 0.19) for the default
COSMO-RS computations of coumarin solubility.
4. Conclusions
It was already demonstrated in previous reports that COSMO-RS-DARE offers a sub-
stantial improvement in solubility computations over default COSMO-RS predictions.
Although it requires experimental data for finding the values of its parameters by a fitting
procedure, the linear dependence between the enthalpic and entropic contributions of in-
teraction Gibbs free energy enables using just two parameters for very accurate back-com-
putations of experimental solubility data. In this report, a new range of applications of
COMOS-RS-DARE is demonstrated. The observed discrepancies in the reported solubility
of coumarin in ethanol were resolved based on the temperature trends of interaction
Gibbs free energy values. Outliers can be clearly identified based on interaction parame-
ters, either by the inspection of Gint(T) temperature trends or the values of temperature-
independent components, Hint and Sint. Importantly, Gint was found to be correlated with
popular molecular features related to polarity and hydrogen-bonding forces, which is
consistent with chemical intuition. A univocal validation of this approach was conducted
by providing the results of new measurements of coumarin in neat alcohols. Four solvents
were selected for the direct duplication of molar fraction solubility under saturated con-
ditions, and an additional three were considered for the inspection of the broader trend
within the aliphatic alcohol series. The consistency of the data was discussed, not only in
terms of the comparison of the remeasured solubility data with those already published
but also within the series of structurally similar solvents. The proposed procedure not
Figure 8. The results of the solubility prediction of coumarin in neat alcohols using the COSMO-RS
and COSMO-RS-DARE approaches. The back-computed solubility values with Gint parameters
fully fitted to experimental data were augmented by the ones resulting from the linear relationships
provided in Figure 7.
4. Conclusions
It was already demonstrated in previous reports that COSMO-RS-DARE offers a
substantial improvement in solubility computations over default COSMO-RS predictions.
Although it requires experimental data for finding the values of its parameters by a fitting
procedure, the linear dependence between the enthalpic and entropic contributions of
interaction Gibbs free energy enables using just two parameters for very accurate back-
computations of experimental solubility data. In this report, a new range of applications of
COMOS-RS-DARE is demonstrated. The observed discrepancies in the reported solubility
of coumarin in ethanol were resolved based on the temperature trends of interaction Gibbs
free energy values. Outliers can be clearly identified based on interaction parameters, either
by the inspection of Gint(T) temperature trends or the values of temperature-independent
components, Hint and Sint. Importantly, Gint was found to be correlated with popular
molecular features related to polarity and hydrogen-bonding forces, which is consistent
with chemical intuition. A univocal validation of this approach was conducted by providing
the results of new measurements of coumarin in neat alcohols. Four solvents were selected
for the direct duplication of molar fraction solubility under saturated conditions, and
an additional three were considered for the inspection of the broader trend within the
aliphatic alcohol series. The consistency of the data was discussed, not only in terms
of the comparison of the remeasured solubility data with those already published but
also within the series of structurally similar solvents. The proposed procedure not only
extends the range of applicability of COSMO-RS-DARE but provides a real and useful tool
for consistency tests of already published solubility data. This can be a valuable guide
for planning solubility measurements, reducing experimental efforts for data duplication
or verification and building a coherent solubility database. The procedure can be easily
extended to multicomponent mixtures of solvents.
14. Molecules 2022, 27, 5274 14 of 16
Supplementary Materials: The following supporting information can be downloaded at: https://
www.mdpi.com/article/10.3390/molecules27165274/s1, Table S1: The solubility values of coumarin
(CAS: 91-64-5) expressed as molar fractions (×103) along with the standard deviation values (n = 3),
Table S2: Statistical characteristics of linear regressions exemplified in Figure 8 and used for back-
computations of solubility using COSMO-RS-DARE approach, Table S3: Collection of molecular
descriptors used for determination of linear regression.
Author Contributions: Conceptualization, P.C.; methodology, P.C., T.J. and M.P.; validation, P.C., T.J.
and M.P.; formal analysis, P.C., T.J. and M.P.; investigation, P.C., T.J. and M.P.; resources, P.C., T.J. and
M.P.; data curation, P.C.; writing—original draft preparation, P.C., T.J. and M.P.; writing—review
and editing, P.C., T.J. and M.P.; visualization, P.C.; supervision, P.C.; project administration, P.C. All
authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: All data supporting the reported results are available on request from
the corresponding author.
Conflicts of Interest: The authors declare no conflict of interest.
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