Application of COSMO-RS-DARE as a Tool for Testing Consistency of Solubility Data: Case of Coumarin in Neat Alcohols.

Coumarin is a naturally occurring lactone-type benzopyrone with various applications in the pharmaceutical, food, perfume, and cosmetics industries. This hydrophobic compound is poorly soluble in water but dissolves well in protic organic solvents such as alcohols. Despite the extensive use of coumarin, there are only a few reports documenting its solubility in organic solvents, and some reported data are incongruent, which was the direct impulse for this study. To resolve this problem, a theoretical congruency test was formulated using COSMO-RS-DARE for the determination of intermolecular interaction parameters, which allowed for the identification of outliers as suspicious datasets. The perfect match between back-computed values of coumarin solubility and the experimental ones confirms the reliability of the formulated theoretical approach and its adequacy for testing solubility data consistency. As the final approval, the temperature-related coumarin solubility in seven neat alcohols was determined experimentally. Four solvents (methanol, ethanol, 1-propanol, and 2-propanol) were used for reproducibility purposes, and an additional three (1-butanol, 1-pentanol, and 1-octanol) were used to extend the information on the homologous series. The consistency of this extended solubility dataset is discussed in terms of the comparison of remeasured solubility values with the ones already published and within the series of structurally similar solvents. The proposed procedure extends the range of applicability of COSMO-RS-DARE and provides a real and useful tool for consistency tests of already published solubility data, allowing for the approval/disapproval of existing data and filling gaps in datasets. Linear regressions utilizing a 2D molecular descriptor, SpMin2_Bhm, or the distance between solute and solvent in the Hansen solubility space, Ra, were formulated for the estimation of COMSO-RS-DARE integration parameters.

Solubilization of Trans-Resveratrol in Some Mono-Solvents and Various Propylene Glycol + Water Mixtures.

This research deals with the determination of solubility, Hansen solubility parameters, dissolution properties, enthalpy-entropy compensation, and computational modeling of a naturally-derived bioactive compound trans-resveratrol (TRV) in water, methanol, ethanol, n-propanol, n-butanol, propylene glycol (PG), and various PG + water mixtures. The solubility of TRV in six different mono-solvents and various PG + water mixtures was determined at 298.2-318.2 K and 0.1 MPa. The measured experimental solubility values of TRV were regressed using six different computational/theoretical models, including van't Hoff, Apelblat, Buchowski-Ksiazczak λh, Yalkowsly-Roseman, Jouyban-Acree, and van't Hoff-Jouyban-Acree models, with average uncertainties of less than 3.0%. The maxima of TRV solubility in mole fraction was obtained in neat PG (2.62 × 10-2) at 318.2 K. However, the minima of TRV solubility in the mole fraction was recorded in neat water (3.12 × 10-6) at 298.2 K. Thermodynamic calculation of TRV dissolution properties suggested an endothermic and entropy-driven dissolution of TRV in all studied mono-solvents and various PG + water mixtures. Solvation behavior evaluation indicated an enthalpy-driven mechanism as the main mechanism for TRV solvation. Based on these data and observations, PG has been chosen as the best mono-solvent for TRV solubilization.

Solubility, Hansen Solubility Parameters and Thermodynamic Behavior of Emtricitabine in Various (Polyethylene Glycol-400 + Water) Mixtures: Computational Modeling and Thermodynamics.

This study was aimed to find out the solubility, thermodynamic behavior, Hansen solubility parameters and molecular interactions of an antiviral drug emtricitabine (ECT) in various "[polyethylene glycol-400 (PEG-400) + water]" mixtures. The solubility of ECT in mole fraction was determined at "T = 298.2 to 318.2 K" and "p = 0.1 MPa" using an isothermal method. The experimental solubilities of ECT in mole fraction were validated and correlated using various computational models which includes "Van't Hoff, Apelblat, Yalkowsky-Roseman, Jouyban-Acree and Jouyban-Acree-Van't Hoff models". All the models performed well in terms of model correlation. The solubility of ECT was increased with the raise in temperature in all "PEG-400 + water" mixtures studied. The highest and lowest solubility values of ECT were found in pure PEG-400 (1.45 × 10-1) at "T = 318.2 K" and pure water (7.95 × 10-3) at "T = 298.2 K", respectively. The quantitative values of activity coefficients indicated higher interactions at molecular level in ECT and PEG-400 combination compared with ECT and water combination. "Apparent thermodynamic analysis" showed an "endothermic and entropy-driven dissolution" of ECT in all "PEG-400 + water" combinations studied. The solvation nature of ECT was found an "enthalpy-driven" in each "PEG-400 + water" mixture studied.

Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers.

Solubility parameter models are widely used to select suitable solvents/nonsolvents for polymers in a variety of processing and engineering applications. In this study, we focus on two well-established models, namely, the Hildebrand and Hansen solubility parameter models. Both models are built on the basis of the notion of "like dissolves like" and identify a liquid as a good solvent for a polymer if the solubility parameters of the liquid and the polymer are close to each other. Here we make a critical and quantitative assessment of the accuracy/utility of these two models by comparing their predictions against actual experimental data. Using a data set of 75 polymers, we find that the Hildebrand model displays a predictive accuracy of 60% for solvents and 76% for nonsolvents. The Hansen model leads to a similar performance; on the basis of a data set of 25 polymers for which Hansen parameters are available, we find that it has an accuracy of 67% for solvents and 76% for nonsolvents. The availability of the Hildebrand parameters for a large polymer data set makes it a widely applicable capability, as the Hildebrand parameter for a new polymer may be determined using this data set and machine learning methods as we have done before; the predicted Hildebrand parameter for a new polymer may then be used to determine suitable solvents and nonsolvents. Such predictions are difficult to make with the Hansen model, as the data set of Hansen parameters for polymers is rather small. Nevertheless, the Hildebrand approach must be used with caution. Our analysis shows that while the Hildebrand model has a predictive accuracy of 70-75% for nonpolar polymers, it performs rather poorly for polar polymers (with an accuracy of 57%). Going forward, determination of solvents and nonsolvents for polymers may benefit by developing classification models built directly on the basis of available experimental data sets rather than utilizing the solubility parameter approach, which is limited in versatility and accuracy.

Effect of Tetrabutylammonium Bromide-Based Deep Eutectic Solvents on the Aqueous Solubility of Indomethacin at Various Temperatures: Measurement, Modeling, and Prediction with Three-Dimensional Hansen Solubility Parameters.

Deep eutectic solvents (DESs) have recently been getting a great deal of attention in many fields of science and technology. The objective of this study was to peruse the solubility of indomethacin (IMC) as sparingly soluble drug in some tetrabutylammonium bromide (TBAB)-based DESs (TBAB/ethylene glycol and TBAB/glycerol). The shake flask method has been employed in this study at temperature ranges T = (298.15-313.15) K and atmospheric pressure (pP = 86.6 kPa). The results showed that the solubility of IMC in TBAB/ethylene glycol system was obtained approximately 17,000-fold more than its solubility in water. The solubility data were accurately correlated by the famous local composition activity coefficient models including e-NRTL and UNIQUAC. It was also our aim to evaluate Hansen solubility parameters in IMC solubility prediction. These parameters can help to predict the solvent performance during the manufacturing processes and will be useful in guessing solvent behavior in many other fields of effort. The experimental and the Hansen solubility parameters results are very well matched. In addition, the apparent thermodynamic properties of dissolution and mixing were studied in these solutions based on Van't Hoff and Gibbs equations.

Model Protein Adsorption on Polymers Explained by Hansen Solubility Parameters.

Hansen solubility parameters (HSP) theory has been successful in explaining the wettability of organic solvents on polymer surfaces and miscibility of different polymers. Here, we demonstrate that the amount of bovine serum albumin (BSA) protein adsorption on different polymer surfaces can also be explained by HSP. Interestingly, the HSP of the adsorbed BSA proteins calculated from the protein adsorption data is different than the HSP of native BSA protein itself. The HSP of the adsorbed BSA proteins are more hydrophobic than the native BSA protein. This observation suggested adsorbed BSA proteins are partially denatured and exposed their hydrophobic core toward the polymer surfaces. These results highlight a new strategic direction to understand interaction of protein with a surface: a theoretical approach that compliments experimental approach. The model in this study could be used to predict the amount of BSA adsorption on a polymer or any other solid surface, if the HSP of that surface is known. Further, the model can serve as a prescreen method to identify surfaces that are problematic at the outset and inform subsequent empirical studies to select packaging that will have the least adsorption for the specific biologic application.

Short-time dynamics of lysozyme solutions with competing short-range attraction and long-range repulsion: Experiment and theory.

Recently, atypical static features of microstructural ordering in low-salinity lysozyme protein solutions have been extensively explored experimentally and explained theoretically based on a short-range attractive plus long-range repulsive (SALR) interaction potential. However, the protein dynamics and the relationship to the atypical SALR structure remain to be demonstrated. Here, the applicability of semi-analytic theoretical methods predicting diffusion properties and viscosity in isotropic particle suspensions to low-salinity lysozyme protein solutions is tested. Using the interaction potential parameters previously obtained from static structure factor measurements, our results of Monte Carlo simulations representing seven experimental lysoyzme samples indicate that they exist either in dispersed fluid or random percolated states. The self-consistent Zerah-Hansen scheme is used to describe the static structure factor, S(q), which is the input to our calculation schemes for the short-time hydrodynamic function, H(q), and the zero-frequency viscosity η. The schemes account for hydrodynamic interactions included on an approximate level. Theoretical predictions for H(q) as a function of the wavenumber q quantitatively agree with experimental results at small protein concentrations obtained using neutron spin echo measurements. At higher concentrations, qualitative agreement is preserved although the calculated hydrodynamic functions are overestimated. We attribute the differences for higher concentrations and lower temperatures to translational-rotational diffusion coupling induced by the shape and interaction anisotropy of particles and clusters, patchiness of the lysozyme particle surfaces, and the intra-cluster dynamics, features not included in our simple globular particle model. The theoretical results for the solution viscosity, η, are in qualitative agreement with our experimental data even at higher concentrations. We demonstrate that semi-quantitative predictions of diffusion properties and viscosity of solutions of globular proteins are possible given only the equilibrium structure factor of proteins. Furthermore, we explore the effects of changing the attraction strength on H(q) and η.

A green analytical chemistry approach for lipid extraction: computation methods in the selection of green solvents as alternative to hexane.

There is a great interest in finding alternatives and green solvents in extraction processes to replace petroleum based solvents. In order to investigate these possibilities, computational methods, as Hansen solubility parameters (HSP) and conductor-like screening model for real solvent (COSMO-RS), were used in this work to predict the solvation power of a series of solvents in salmon fish lipids. Additionally, experimental studies were used to evaluate the performance in lipids extraction using 2-methyltetrahydrofurane, cyclopentyl methyl ether, dimethyl carbonate, isopropanol, ethanol, ethyl acetate, p-cymene and d-limonene compared with hexane. Lipid classes of extracts were obtained by using high performance thin-layer chromatography (HPTLC), whereas gas chromatography with a flame ionization detector (GC/FID) technique was employed to obtain fatty acid profiles. Some differences between theoretical and experimental results were observed, especially regarding the behavior of p-cymene and d-limonene, which separate from the predicted capability. Results obtained from HPTLC indicated that p-cymene and d-limonene extract triglycerides (TAGs) and diglycerides (DAGs) at levels of 73 and 19%, respectively, whereas the other studied extracts contain between 75 and 76% of TAGs and between 16 and 17% of DAGs. Fatty acid profiles, obtained by using GC-FID, indicated that saturated fatty acids (SFAs) between 19.5 and 19.9% of extracted oil, monounsaturated fatty acids (MUFAs) in the range between 43.5 and 44.9%, and PUFAs between 31.2 and 34.6% were extracted. p-Cymene and limonene extracts contained lower percentages than the other studied solvents of some PUFAs due probably to the fact that these unsaturated fatty acids are more susceptible to oxidative degradation than MUFAs. Ethyl acetate has been found to be the best alternative solvent to hexane for the extraction of salmon oil lipids. Graphical Abstract ᅟ.

To gel or not to gel: correlating molecular gelation with solvent parameters.

Rational design of small molecular gelators is an elusive and herculean task, despite the rapidly growing body of literature devoted to such gels over the past decade. The process of self-assembly, in molecular gels, is intricate and must balance parameters influencing solubility and those contrasting forces that govern epitaxial growth into axially symmetric elongated aggregates. Although the gelator-gelator interactions are of paramount importance in understanding gelation, the solvent-gelator specific (i.e., H-bonding) and nonspecific (dipole-dipole, dipole-induced and instantaneous dipole induced forces) intermolecular interactions are equally important. Solvent properties mediate the self-assembly of molecular gelators into their self-assembled fibrillar networks. Herein, solubility parameters of solvents, ranging from partition coefficients (log P), to Henry's law constants (HLC), to solvatochromic parameters (ET(30)), and Kamlet-Taft parameters (ß, α and π), and to Hansen solubility parameters (δp, δd, δh), are correlated with the gelation ability of numerous classes of molecular gelators. Advanced solvent clustering techniques have led to the development of a priori tools that can identify the solvents that will be gelled and not gelled by molecular gelators. These tools will greatly aid in the development of novel gelators without solely relying on serendipitous discoveries. These tools illustrate that the quest for the universal gelator should be left in the hands of Don Quixote and as researchers we must focus on identifying gelators capable of gelling classes of solvents as there is likely no one gelator capable of gelling all solvents.

Freezing lines of colloidal Yukawa spheres. II. Local structure and characteristic lengths.

Using the Rogers-Young (RY) integral equation scheme for the static pair correlation functions combined with the liquid-phase Hansen-Verlet freezing rule, we study the generic behavior of the radial distribution function and static structure factor of monodisperse charge-stabilized suspensions with Yukawa-type repulsive particle interactions at freezing. In a related article, labeled Paper I [J. Gapinski, G. Nägele, and A. Patkowski, J. Chem. Phys. 136, 024507 (2012)], this hybrid method was used to determine two-parameter freezing lines for experimentally controllable parameters, characteristic of suspensions of charged silica spheres in dimethylformamide. A universal scaling of the RY radial distribution function maximum is shown to apply to the liquid-bcc and liquid-fcc segments of the universal freezing line. A thorough analysis is made of the behavior of characteristic distances and wavenumbers, next-neighbor particle coordination numbers, osmotic compressibility factor, and the Ravaché-Mountain-Streett minimum-maximum radial distribution function ratio.

Lignin dissolution in dialkylimidazolium-based ionic liquid-water mixtures.

Lignin dissolution in dialkylimidazolium-based ionic liquid (IL)-water mixtures (40wt%-100wt% IL content) at 60°C was investigated. The IL content and type are found to considerably affect lignin solubility. For the IL-water mixtures except 1-butyl-3-methylimidazolium tetrafluoroborate ([C4C1im]BF4), the maximum lignin solubility can be achieved at 70wt% IL content. Lignin solubility in IL-water mixtures with different cations follows the order 1-butyl-3-methylimidazolium ([C4C1im](+))>1-hexyl-3-methylimidazolium ([C6C1im](+))>1-ethyl-3-methylimidazolium ([C2C1im](+))>1-octyl-3-methylimidazolium ([C8C1im](+))>1-butyl-3-ethylimidazolium ([C4C2im](+))>1-butyl-3-propylimidazolium ([C4C3im](+)). For IL mixtures with different anions, lignin solubility decreases in the following order: methanesulfonate (MeSO3(-))>acetate (MeCO2(-))>bromide (Br(-))>dibutylphosphate (DBP(-)). Evaluation using the theory of Hansen solubility parameter (HSP) is consistent with the experimental results, suggesting that HSP can aid in finding the appropriate range of IL content for IL-water mixtures. However, HSP cannot be used to evaluate the effect of IL type on lignin solubility.

Ionic asymmetry and solvent excluded volume effects on spherical electric double layers: a density functional approach.

In this article, we present a classical density functional theory for electrical double layers of spherical macroions that extends the capabilities of conventional approaches by accounting for electrostatic ion correlations, size asymmetry, and excluded volume effects. The approach is based on a recent approximation introduced by Hansen-Goos and Roth for the hard sphere excess free energy of inhomogeneous fluids [J. Chem. Phys. 124, 154506 (2006); Hansen-Goos and Roth, J. Phys.: Condens. Matter 18, 8413 (2006)]. It accounts for the proper and efficient description of the effects of ionic asymmetry and solvent excluded volume, especially at high ion concentrations and size asymmetry ratios including those observed in experimental studies. Additionally, we utilize a leading functional Taylor expansion approximation of the ion density profiles. In addition, we use the mean spherical approximation for multi-component charged hard sphere fluids to account for the electrostatic ion correlation effects. These approximations are implemented in our theoretical formulation into a suitable decomposition of the excess free energy which plays a key role in capturing the complex interplay between charge correlations and excluded volume effects. We perform Monte Carlo simulations in various scenarios to validate the proposed approach, obtaining a good compromise between accuracy and computational cost. We use the proposed computational approach to study the effects of ion size, ion size asymmetry, and solvent excluded volume on the ion profiles, integrated charge, mean electrostatic potential, and ionic coordination number around spherical macroions in various electrolyte mixtures. Our results show that both solvent hard sphere diameter and density play a dominant role in the distribution of ions around spherical macroions, mainly for experimental water molarity and size values where the counterion distribution is characterized by a tight binding to the macroion, similar to that predicted by the Stern model.

Application of carrier and plasticizer to improve the dissolution and bioavailability of poorly water-soluble baicalein by hot melt extrusion.

The objective of this study was to develop a suitable formulation for baicalein (a poorly water-soluble drug exhibiting high melting point) to prepare solid dispersions using hot melt extrusion (HME). Proper carriers and plasticizers were selected by calculating the Hansen solubility parameters, evaluating melting processing condition, and measuring the solubility of obtained melts. The characteristic of solid dispersions prepared by HME was evaluated. The dissolution performance of the extrudates was compared to the pure drug and the physical mixtures. Physicochemical properties of the extrudates were characterized by differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), and Fourier transform infrared spectroscopy (FTIR). Relative bioavailability after oral administration in beagle dogs was assessed. As a result, Kollidon VA64 and Eudragit EPO were selected as two carriers; Cremophor RH was used as the plasticizer. The dissolution of all the extrudates was significantly improved. DSC and PXRD results suggested that baicalein in the extrudates was amorphous. FTIR spectroscopy revealed the interaction between drug and polymers. After oral administration, the relative bioavailability of solid dispersions with VA64 and EPO was comparative, about 2.4- and 2.9-fold greater compared to the pure drug, respectively.

Data mining of solubility parameters for computational prediction of drug-excipient miscibility.

Abstract Computational data mining is of interest in the pharmaceutical arena for the analysis of massive amounts of data and to assist in the management and utilization of the data. In this study, a data mining approach was used to predict the miscibility of a drug and several excipients, using Hansen solubility parameters (HSPs) as the data set. The K-means clustering algorithm was applied to predict the miscibility of indomethacin with a set of more than 30 compounds based on their partial solubility parameters [dispersion forces (δd), polar forces (δp) and hydrogen bonding (δh)]. The miscibility of the compounds was determined experimentally, using differential scanning calorimetry (DSC), in a separate study. The results of the K-means algorithm and DSC were compared to evaluate the K-means clustering prediction performance using the HSPs three-dimensional parameters, the two-dimensional parameters such as volume-dependent solubility (δv) and hydrogen bonding (δh) and selected single (one-dimensional) parameters. Using HSPs, the prediction of miscibility by the K-means algorithm correlated well with the DSC results, with an overall accuracy of 94%. The prediction accuracy was the same (94%) when the two-dimensional parameters or the hydrogen-bonding (one-dimensional) parameter were used. The hydrogen-bonding parameter was thus a determining factor in predicting miscibility in such set of compounds, whereas the dispersive and polar parameters had only a weak correlation. The results show that data mining approach is a valuable tool for predicting drug-excipient miscibility because it is easy to use, is time and cost-effective, and is material sparing.

High throughput screening: an in silico solubility parameter approach for lipids and solvents in SLN preparations.

OBJECTIVE: The present paper describes an in silico solubility behavior of drug and lipids, an essential screening study in preparation of solid lipid nanoparticles (SLN). MATERIALS AND METHODS: Ciprofloxacin HCl was selected as a model drug along with 11 lipids and 5 organic solvents. In silico miscibility study of drug/lipid/solvent was performed using Hansen solubility parameter approach calculated by group contribution method of Van Krevelen and Hoftyzer. Predicted solubility was validated by determining solubility of lipids in various solvent at different temperature range, while miscibility of drug in lipids was determined by apparent solubility study and partition experiment. RESULTS AND DISCUSSION: The presence of oxygen and OH functionality increases the polarity and hydrogen bonding possibilities of the compound which has reflected the highest solubility parameter values for Geleol and Capmul MCM C8. Ethyl acetate, Geleol and Capmul MCM C8 was identified as suitable organic solvent, solid lipid and liquid lipid respectively based on a solubility parameter approach which was in agreement with the result of an apparent solubility study and partition coefficient. CONCLUSION: These works demonstrate the validity of solubility parameter approach and provide a feasible predictor to the rational selection of excipients in designing SLN formulation.

Development and characterization of a new oral dapsone nanoemulsion system: permeability and in silico bioavailability studies.

BACKGROUND: Dapsone is described as being active against Mycobacterium leprae, hence its role in the treatment of leprosy and related pathologies. Despite its therapeutic potential, the low solubility of dapsone in water results in low bioavailability and high microbial resistance. Nanoemulsions are pharmaceutical delivery systems derived from micellar solutions with a good capacity for improving absorption. The aim of this work was to develop and compare the permeability of a series of dapsone nanoemulsions in Caco-2 cell culture against that of effective permeability in the human body simulated using Gastroplus™ software. METHODS AND RESULTS: The release profiles of the dapsone nanoemulsions using different combinations of surfactants and cosolvent showed a higher dissolution rate in simulated gastric and enteric fluid than did the dispersed dapsone powder. The drug release kinetics were consistent with a Higuchi model. CONCLUSION: This comparison of dapsone permeability in Caco-2 cells with effective permeability in the human body simulated by Gastroplus showed a good correlation and indicates potential improvement in the biodisponibility of dapsone using this new system.

Retrostructural model to predict biomass formulations for barrier performance.

Barrier performance and retrostructural modeling of the macromolecular components demonstrate new design principles for film formulations based on renewable wood hydrolysates. Hardwood hydrolysates, which contain a fair share of lignin coexisting with poly- and oligosaccharides, offer excellent oxygen-barrier performance. A Hansen solubility parameter (HSP) model has been developed to convert the complex hydrolysate structural compositions into relevant matrix oxygen-permeability data allowing a systematic prediction of how the biomass should be formulated to generate an efficient barrier. HSP modeling suggests that the molecular packing ability plays a key role in the barrier performance. The actual size and distribution of free volume holes in the matrices were quantified in the subnanometer scale with Positron annihilation lifetime spectroscopy (PALS) verifying the affinity-driven assembly of macromolecular segments in a densely packed morphology and regulating the diffusion of small permeants through the matrix. The model is general and can be adapted to determine the macromolecular affinities of any hydrolysate biomass based on chemical composition.

A new expanded solubility parameter approach.

The partial or Hansen solubility parameters (HSP) are important properties of the various substances and very useful tools for the selection of their solvents or the prediction of their behaviour in numerous applications. Their design and evaluation relies on the basic rule of "similarity matching" for solubility. The present work attempts to enhance the capacity of HSPs by incorporating into their evaluation the other basic rule of solubility, namely, the rule of "complementarity matching". This is done in a simple and straightforward manner by splitting the hydrogen bonding HSP into its acidic or proton donor component and its basic or proton acceptor one. The splitting is based on the third σ-moments of the screening charge distributions or sigma profiles of the quantum-mechanics based COSMO-RS theory. The whole development and application does not involve any sophisticated calculations or any strong specific background. The new method has been applied to a variety of solubility data for systems of pharmaceutical interest in order to verify the significant improvement over the classical HSP approach. The application of the new method requires, of course, the knowledge of the HSPs. For this reason, in Appendix A is presented an updated version of a robust and reliable group-contribution method for the calculation of the HSPs. The key features of this combined tool are critically discussed.

Comparative modeling of UDP-N-acetylmuramoyl-glycyl-D-glutamate-2, 6-diaminopimelate ligase from Mycobacterium leprae and analysis of its binding features through molecular docking studies.

Leprosy is an infectious disease caused by Mycobacterium leprae. The increasing drug and multi-drug resistance of M. leprae enforce the importance of finding new drug targets. Mycobacterium has unusually impermeable cell wall that contributes to considerable resistance to many drugs. Peptidoglycan is an important component of the cell wall of M. leprae. UDP-N-acetylmuramoyl-glycyl-D-glutamate-2, 6-diaminopimelate ligase (MurE) plays a crucial role in the peptidoglycan biosynthesis and hence it could be considered as a potential drug target for leprosy. Structure of this enzyme for M. leprae has not yet been elucidated. We modeled the three-dimensional structure of MurE from M. leprae using comparative modeling methods based on the X-ray crystal structure of MurE from E. coli and validated. The 3D-structure of M. leprae MurE enzyme was docked with its substrates meso-diaminopimelic acid (A2pm) and UDP-N-acetyl muramoyl-glycyl-D- glutamate (UMGG) and its product UDP-N-acetyl muramoyl-glycyl-D-glu-meso-A(2)pm (UTP) and also with ATP. The docked complexes reveal the amino acids responsible for binding the substrates. Superposition of these complex structures suggests that carboxylic acid group of UMGG is positioned in proximity to γ-phosphate of the ATP to facilitate the formation of acylphosphate intermediate. The orientation of an amino group of A(2)pm facilitates the nucleophilic attack to form the product. Overall, the proposed model together with its binding features gained from docking studies could help to design a truly selective ligand inhibitor specific to MurE for the treatment of leprosy.

Hansen solubility parameter as a tool to predict cocrystal formation.

The objective of this study was to investigate whether the miscibility of a drug and coformer, as predicted by Hansen solubility parameters (HSPs), can indicate cocrystal formation and guide cocrystal screening. It was also our aim to evaluate various HSPs-based approaches in miscibility prediction. HSPs for indomethacin (the model drug) and over thirty coformers were calculated according to the group contribution method. Differences in the HSPs between indomethacin and each coformer were then calculated using three established approaches, and the miscibility was predicted. Subsequently, differential scanning calorimetry was used to investigate the experimental miscibility and cocrystal formation. The formation of cocrystals was also verified using liquid-assisted grinding. All except one of the drug-coformers that were predicted to be miscible were confirmed experimentally as miscible. All tested theoretical approaches were in agreement in predicting miscibility. All systems that formed cocrystals were miscible. Remarkably, two new cocrystals of indomethacin were discovered in this study. Though it may be necessary to test this approach in a wide range of different coformer and drug compound types for accurate generalizations, the trends with tested systems were clear and suggest that the drug and coformer should be miscible for cocrystal formation. Thus, predicting the miscibility of cocrystal components using solubility parameters can guide the selection of potential coformers prior to exhaustive cocrystal screening work.