Logarithm Of Solubility Research Articles

Graph Neural Networks for Predicting Solubility in Diverse Solvents Using MolMerger Incorporating Solute-Solvent Interactions.

The prediction of solubility is a complex and challenging physicochemical problem that has tremendous implications for the chemical and pharmaceutical industry. Recent advancements in machine learning methods have provided a great scope for predicting the reliable solubility of a large number of molecular systems. However, most of these methods rely on using physical properties obtained from experiments and expensive quantum chemical calculations. Here, we developed a method that utilizes a graphical representation of solute-solvent interactions using "MolMerger," which captures the strongest polar interactions between molecules using Gasteiger charges and creates a graph incorporating the true nature of the system. Using these graphs as input, a neural network learns the correlation between the structural properties of a molecule in the form of node embedding and its physicochemical properties as the output. This approach has been used to calculate molecular solubility by predicting the Log solubility values of various organic molecules and pharmaceuticals in diverse sets of solvents.

Evidence of strobilurin fungicides and their metabolites in Dongjiang River ecosystem, southern China: Bioaccumulation and ecological risks

Despite the widespread application of strobilurin fungicides (SFs) in agriculture, little is known about their distribution and bioaccumulation in aquatic ecosystems. In this study, the concentrations of 12 SFs and two of their metabolites were determined in abiotic (water and sediment; n = 83) and biotic (plant, algae, zooplankton, and fish; n = 123) samples collected from a subtropical freshwater ecosystem, namely, Dongjiang River wetland, in southern China. Among the 12 SFs measured, azoxystrobin (AZ) was the major fungicide found in surface water (median: 2.20 ng/L) and sediment (0.064 ng/g dry wt.). Azoxystrobin acid (AZ-acid), a metabolite of AZ, was the major analyte in the plant samples and had a median concentration at 0.36 ng/g dry wt. In algae and zooplankton, (Z)-metominostrobin was the predominant fungicide and had median concentrations of 3.52 and 5.55 ng/g dry wt., respectively. In fish muscle, dimoxystrobin (DIMO) was the major SF and had a median concentration of 0.47 ng/g dry wt. The bioconcentration factor (BCF) values of AZ-acid, trifloxystrobin (TFS), and pyraclostrobin (PYR) in algae and zooplankton and AZ-acid, PYR, TFS, TFS-acid, picoxystrobin, and DIMO in fish muscle exceeded 1000 L/kg (algae, zooplankton, and fish concentrations were expressed on a dry weight basis), suggesting that these fungicides can accumulate in biota. A positive association between log BCFs of SFs in fish and logKow of SFs and a negative correlation between log BCFs and the log solubility index were observed. Additionally, the risk quotient (RQ) was calculated to evaluate the potential ecotoxicological risk of SFs to different aquatic organisms (algae, zooplankton, and fish). The PYR and DIMO concentrations at 19 sampling sites had RQ values >0.1, indicating moderate ecotoxicological risks to aquatic organisms. This study is the first to document the widespread occurrence of SFs and their metabolites in aquatic ecosystems and to elucidate the bioaccumulation potential of SFs in aquatic organisms.

Extended Hildebrand Solubility Approach and Inverse Kirkwood–Buff Integrals Method Applied to Chloroxine Solubility in Several Blended Solvents

ABSTRACT Extended Hildebrand solubility approach (EHSA) was used in this work to analyse the chloroxine solubility in mixtures at temperature of 298.15 K. A good prediction results of EHSA were observed to correlate the interaction parameter (W) and solubility parameter of blends in the absence of chloroxine (δ 1+2). Nonetheless, the forecasting outcomes of EHSA were similar with that attained when natural logarithm of solubility (lnx 3) was associated with δ 1+2. Additionally, the local mole fraction of ethyl acetate and n-propanol/methanol/isopropanol/ethanol in the vicinity of chloroxine were quantitatively derived by the inverse Kirkwood–Buff integrals method. It could be conjectured that in the alcohol-rich solutions, the interactions of acidic sites of alcohols on basic sites of chloroxine have crucial responsibility for the solvation. It is remarkable the present work does expand the preferential solvation analysis of chloroxine by the particular solvent species in the ethyl acetate + alcohol mixtures.

Solubility of wodginite, titanowodginite, microlite, pyrochlore, columbite-(Mn) and tantalite-(Mn) in flux-rich haplogranitic melts between 700° and 850 °C and 200 MPa

Ore minerals of niobium and tantalum are typically associated with pegmatites and rare metal granites; these include columbite, tantalite, wodginite, titanowodginite, microlite and pyrochlore. Solubility and crystallization mechanisms for columbite-(Mn) and tantalite-(Mn) have been extensively studied in haplogranitic melts, with little research into other ore minerals. In this study the solubilities of wodginite, titanowodginite, microlite and pyrochlore are compared to those for columbite-(Mn) and tantalite-(Mn) in a flux-rich haplogranitic melt of alumina saturation index (ASI) 1.0 (ASILi of 0.83) at 700–850 °C and 200 MPa. The effect of melt composition on the solubilities of wodginite, titanowodginite, and microlite compared to tantalite-(Mn) is also investigated in highly fluxed haplogranitic melts of ASI 1.0, 1.10, and 1.24 (ASILi of 0.83, 0.90, 1.02), at 700 °C and 800 °C and 200 MPa. The log solubility product (logKsp) at 750 °C and melt ASI of 1.0 is highest for tantalite-(Mn) (−2.32 mol2/kg2) followed by columbite-(Mn) (−2.68 mol2/kg2), and pyrochlore (−3.71 mol3/kg3) titanowodginite (−3.73 mol3/kg3), wodginite (−3.77 mol3/kg3), and microlite (−3.78 mol3/kg3), the latter four of which are almost identical within error. However, solubility can also be expressed as a mineral-melt partition coefficient, with higher partition coefficients reflecting lower solubilities. The tantalum mineral-melt partition coefficients of wodginite (27.0), titanowodginite (30.2), and tantalite-(Mn) (29.6) are identical within error; microlite is higher (80.3, reflected by lower concentrations of tantalum in the melt for stoichiometric saturation) because it contains a major melt cation, sodium. The niobium mineral-melt partition coefficient for columbite-(Mn) (66.1) is higher than for pyrochlore (50.1). Wodginite, titanowodginite, pyrochlore, columbite-(Mn) and tantalite-(Mn) have similar temperature and melt composition dependences, but conversely, microlite solubility increases with ASI. As all studied minerals have been shown to have similar relative solubilities at stoichiometric saturation, it can be concluded that, in general, the presence of bivalent (Ca, Mn, Fe) and some tetravalent cations (Sn, Ti) control which tantalum and niobium phases crystallize in rare metal deposits.

Novel high/low solubility classification methods for new molecular entities

This research describes a rapid solubility classification approach that could be used in the discovery and development of new molecular entities. Compounds (N=635) were divided into two groups based on information available in the literature: high solubility (BDDCS/BCS 1/3) and low solubility (BDDCS/BCS 2/4). We established decision rules for determining solubility classes using measured log solubility in molar units (MLogSM) or measured solubility (MSol) in mg/ml units. ROC curve analysis was applied to determine statistically significant threshold values of MSol and MLogSM. Results indicated that NMEs with MLogSM>⿿3.05 or MSol>0.30mg/mL will have ⿥85% probability of being highly soluble and new molecular entities with MLogSM⿤⿿3.05 or MSol⿤0.30mg/mL will have ⿥85% probability of being poorly soluble. When comparing solubility classification using the threshold values of MLogSM or MSol with BDDCS, we were able to correctly classify 85% of compounds. We also evaluated solubility classification of an independent set of 108 orally administered drugs using MSol (0.3mg/mL) and our method correctly classified 81% and 95% of compounds into high and low solubility classes, respectively. The high/low solubility classification using MLogSM or MSol is novel and independent of traditionally used dose number criteria.

BDDCS Applied to Over 900 Drugs

Here, we compile the Biopharmaceutics Drug Disposition Classification System (BDDCS) classification for 927 drugs, which include 30 active metabolites. Of the 897 parent drugs, 78.8% (707) are administered orally. Where the lowest measured solubility is found, this value is reported for 72.7% (513) of these orally administered drugs and a dose number is recorded. The measured values are reported for percent excreted unchanged in urine, LogP, and LogD (7.4) when available. For all 927 compounds, the in silico parameters for predicted Log solubility in water, calculated LogP, polar surface area, and the number of hydrogen bond acceptors and hydrogen bond donors for the active moiety are also provided, thereby allowing comparison analyses for both in silico and experimentally measured values. We discuss the potential use of BDDCS to estimate the disposition characteristics of novel chemicals (new molecular entities) in the early stages of drug discovery and development. Transporter effects in the intestine and the liver are not clinically relevant for BDDCS class 1 drugs, but potentially can have a high impact for class 2 (efflux in the gut, and efflux and uptake in the liver) and class 3 (uptake and efflux in both gut and liver) drugs. A combination of high dose and low solubility is likely to cause BDDCS class 4 to be underpopulated in terms of approved drugs (N = 53 compared with over 200 each in classes 1-3). The influence of several measured and in silico parameters in the process of BDDCS category assignment is discussed in detail.

The stabilities of protein crystals.

We describe a model for protein crystallization equilibria. The model includes four terms, (1) protein translational entropy opposes crystallization, (2) proteins are attracted to each other by a nonelectrostatic contact free energy favoring crystallization, (3) proteins in the crystal repel each other but, to a greater extent, attract counterions sequestered in the crystal, which favors crystallization, and (4) the translational entropy of the counterions opposes their sequestration into the crystal, opposing crystallization. We treat the electrostatics using the nonlinear Poisson-Boltzmann equation, and we use unit cell information from native protein crystals to determine the boundary conditions. This model predicts the stabilities of protein crystals as functions of temperature, pH, and salt concentrations, in good agreement with the data of Pusey et al. on tetragonal and orthorhombic crystal forms of lysozyme. The experiments show a weak dependence of crystal solubility on pH. According to the model, this is because the entropic cost to neutralize the crystal is compensated by favorable protein-salt interactions. Experiments also show that adding salt stabilizes the crystal. Cohn's empirical law predicts that the logarithm of solubility should be a linear function of salt. The present theory predicts nonlinearity, in better agreement with the experiments. The model shows that the salting out phenomena is not due to more counterion shielding but to lowered counterion translational entropy. Models of this type may help guide faster and better ways to crystallize proteins.

Effect of temperature on the solubility of haemoglobin modified with acetyl-3,5-dibromosalicylic acid

Haemoglobin A was acetylated using acetyl-3,5-dibromosalicylic (dibromoaspirin). The acetylated haemoglobin showed enhanced solubility compared to the unmodified haemoglobin and its solubility was found to increase with temperature in the range 13°-37°C. From the plot of log solubility against the reciprocal of temperature, the DH° was calculated to be 23.74 and 30.06 kJmol-1, for the modified and unmodified haemoglobin respectively. This indicates a reduction in the DH° for the modified species. Since the solubility of haemoglobin is enhanced by acetylation with dibromoaspirin, dibromoaspirin might be an effective antisickling agent when administered at optimum temperature. Key words: Haemoglobin, acetyl-3,5-dibromosalicylic acid, protein, sickle cell anaemia, antisickling agent.

Solubility and phase transitions in the water-protein-salt system

The previously derived formulas for the curves corresponding to sol-gel, liquid-liquid, and liquid-solid phase transitions, which correlate the critical molar composition of the water-protein-salt system with individual characteristic features of its component (protein charge z, the number of ions adsorbed v, the function of electrolyte activity A) are presented as curves in ordinary coordinates of protein solubility logS against salt concentration m3. Tendencies in changes in phase transition lines versus the v, z, and v/z ratio have been determined. Correlations of the salting-out curve and the salting-out coefficient with phase transitions are discussed.

Thermodynamic properties of soddyite from solubility and calorimetry measurements

The release of uranium from geologic nuclear waste repositories under oxidizing conditions can only be modeled if the thermodynamic properties of the secondary uranyl minerals that form in the repository setting are known. Toward this end, we synthesized soddyite ((UO 2) 2(SiO 4)(H 2O) 2), and performed solubility measurements from both undersaturation and supersaturation. The solubility measurements rigorously constrain the value of the solubility product of synthetic soddyite, and consequently its standard-state Gibbs free energy of formation. The log solubility product (lg K sp) with its error (1 σ) is (6.43 + 0.20/−0.37), and the standard-state Gibbs free energy of formation is (−3652.2 ± 4.2 (2 σ)) kJ mol −1. High-temperature drop solution calorimetry was conducted, yielding a calculated standard-state enthalpy of formation of soddyite of (−4045.4 ± 4.9 (2 σ)) kJ · mol −1. The standard-state Gibbs free energy and enthalpy of formation yield a calculated standard-state entropy of formation of soddyite of (−1318.7 ± 21.7 (2 σ)) J · mol −1 · K −1. The measurements and associated thermodynamic calculations not only describe the T = 298 K stability and solubility of soddyite, but they also can be used in predictions of repository performance through extrapolation of these properties to repository temperatures.

Kinetic Studies of Synthetic Metaschoepite under Acidic Conditions in Batch and Flow Experiments

The weathering and corrosion of depleted uranium (DU) forms a complex series of oxidation reactions, ultimately resulting in metaschoepite, UO3.2H2O. The present work focused on studying the dissolution rate of synthetic UO3. 2H2O using batch and flow-through reactors. Under acidic conditions (pH = 4.4-5.4), atmospheric CO2, room temperature, and 0.1 mionic strength,the log solubility product, log Ksp = 5.26 at equilibrium and a pH-dependent rate law Ro = (0.30 +/- 0.15)[H+]0.83+/-0.1 were established. For consistency, these results were incorporated into the computer program PHREEQC 2.6, and the experimental conditions were simulated. There is generally good agreement between the experimental results and the modeled results. Batch experiments revealed a fast dissolution rate of UO3.2H20 in the first hour, followed by fluctuations in uranium concentration before equilibrium was attained after 3000 h.

Estimation of the ethanol/water solubility profile from the octanol/water partition coefficient

While the ethanol/water solubility profiles of very polar and very non-polar drugs are monotonic, many semi-polar drugs show a maximum solubility at an ethanol volume fraction ( f max) between 0 and 1. A sigmoidal relationship was observed between the value of f max and the log of the octanol/water partition coefficient (log K ow) of the solute. This relationship reasonably predicts the value of the volume fraction of ethanol that gives maximum solubility ( f max). Combining this sigmoidal relationship with the previously reported linear relationship between the log K ow and the initial slope of the plot of log solubility versus ethanol composition [Li, A., Yalkowsky, S.H., 1994. Solubility of organic solutes in ethanol/water mixtures. J. Pharm. Sci. 83, 1735–1740] enables the estimation of the total ethanol/water solubility profile.

Mathematical correlation of naproxen solubilities in organic solvents with the abraham solvation parameter model

The Abraham solvation parameter model is used to calculate the numerical values of the solute descriptors for naproxen from experimental solubilities in organic solvents. The solute descriptors are denoted as follows: E is the solute excess molar refraction, V is McGowan volume of the solute, A and B are measures of the solute hydrogen-bond acidity and hydrogen-bond basicity, respectively, S is the solute dipolarity/polarizability descriptor and L is the logarithm of solute gas phase dimensionless Ostwald partition coefficient into hexadecane at 298 K. We estimate E as 1.510 and calculate V as 1.7821, and then solve a total of 40 equations to yield S = 2.022, A = 0.600, B = 0.673 and L = 9.207. These descriptors reproduce the observed log solubility ratios to within a standard deviation of only 0.073 log units.

Designing for Topical Delivery: Prodrugs Can Make the Difference

AbstractFor Abstract see ChemInform Abstract in Full Text.

Solubility of Echium, Borage, and Lunaria Seed Oils in Compressed CO2

The solubility of borage, echium, and lunaria oils in compressed CO2 was measured using the dynamic method. Pressure and temperature were varied from (60 to 300) bar and (10 to 55) °C, respectively. The solubilities were compared to those of other vegetable oils and were correlated using the density-based model proposed by Chrastil. As predicted by the model, a linear relationship between the logarithm of solubility and the logarithm of solvent density was obtained. Average deviation between measured and calculated solubility did not exceed 14%.

Solubilization by cosolvents: Establishing useful constants for the log–linear model

The purpose of this study was to develop constants for the log–linear cosolvent model, thereby allowing accurate prediction of solubilization in the most common pharmaceutical cosolvents: propylene glycol, ethanol, polyethylene glycol 400, and glycerin. The solubilization power ( σ) of each cosolvent was determined for a large number of organic compounds from the slope of their log–solubility vs. cosolvent volume fraction plots. The solubilization data at room temperature were either experimentally determined or obtained from the literature. The slopes of the nearly linear relationship between solubilization power and solute hydrophobicity (log K ow) were obtained by linear regression analysis for each considered cosolvent. Thus, knowing or calculating a compound's partition coefficient is all that is needed to predict solubilization.

Modeling the Partition of Volatile Aroma Compounds from a Cloud Emulsion

Parameters determining the partitioning behavior of volatile compounds between a cloud emulsion and the gas phase were measured under static equilibrium headspace conditions, using volatiles (e.g., ethyl hexanoate, cymene, and octanol) representing different volatilities and different degrees of hydrophobicity. The significant factors were the molecular characteristics of the volatile and the concentration of the oil phase. The nature of the lipid (C8 and C12 triglycerides), particle size, and emulsifier type (modified starch and gum arabic) did not significantly alter volatile partitioning. An empirical model based on the partition behavior and physicochemical parameters of 67 volatile compounds was produced. This predicted the partition of volatiles (R(2) = 0.83) in cloud emulsions as a function of lipid content. The significant terms (P < 0.05) in the empirical model were Log P, Log solubility, the dipole vector, and the oil fraction.

IUPAC-NIST Solubility Data Series. 75. Nonmetals in Liquid Alkali Metals

have several physical which favor their use in a number of important applications. For example, their large temperature range and their excellent are important for use as media. They are used in large nuclear reactors in which hundreds of tons of are circulating, and in small parts of engines for cooling of valves. Since these metals are among the most electropositive elements, several of them (Li, can be used in high specific capacity and high energy density batteries at moderately elevated temperatures. The compatibility of metallic constructional materials which are used to contain the is strongly influenced by present in the The physical of the are also influenced by dissolved substances. Several dissolved in are able to form ternary compounds with components of the constructional materials. Thus, corrosion and compatibility studies have been accompanied by extensive chemical work related to the of non-metallic substances in All available data of nonmetallic elements and some of their compounds in the five solvents (Li, K, Rb, and Cs) are collected and compiled. Original publications with reliable data and information on the methods used to generate them are reported in individual Compilations. When numerical data are not given in a publication, the data are often read out from figures and converted into numerical data by the compilers. The precision of this procedure is indicated in the Compilations under Estimated Error. Evaluated data are tabulated at the end of the Critical Evaluations: if there is agreement of at least two independent studies within the experimental error, the values are assigned to the “recommended” category. Values are assigned as “tentative,” if only one reliable result was reported, or if the mean value of two or more reliable studies was outside the error limits. In the tabulation, three, two, or one significant figures are assigned for respective precisions that are better than ±1% and ±10% and worse than ±10%. If necessary, the are recalculated into mol %. The completeness of this investigation of the literature has been confirmed and extended by studying several reviews dealing with the chemistry of substances in the data are sometimes measured under parameters, which are not standard conditions of such measurements. Frequently measurements are performed under constrained pressure. The of noble gases or other gases, which do not form compounds with the depends on the gas pressures. This dependency is documented in the data sheets. Schematic phase diagrams are presented in systems for which they assist the understanding of the data and the conclusions. They are based on the most recent state of knowledge and generally presented in the Critical Evaluations. Some diagrams are shown in form of a log versus reciprocal temperature function. These figures illustrate the larger scatter of data for systems in which interfering reactions cause unstable behavior of While several are well defined substances, other systems need still additional studies to define the equilibrium state compound. One should realize that estimations of the stoichiometry and thermal stability of ternary compounds are experimentally difficult, and their results are often uncertain.

Prediction of C60 Solubilities from Solvent Molecular Structures

Models predicting fullerene solubility in 96 solvents at 298 K were developed using multiple linear regression and feed-forward computational neural networks (CNN). The data set consisted of a diverse set of solvents with solubilities ranging from -3.00 to 2.12 log (solubility) where solubility = (1 x 10(4))(mole fraction of C60 in saturated solution). Each solvent was represented by calculated molecular structure descriptors. A pool of the best linear models, as determined by rms error, was developed, and a CNN model was developed for each of the linear models. The best CNN model was chosen based on the lowest value of a specified cost function and had an architecture of 9-3-1. The 76-compound training set for this model had a root-mean-square error of 0.255 log solubility units, while the 10-compound cross-validation set had an rms error of 0.253. The 10-compound external prediction set had an rms error of 0.346 log solubility units.

Solubility of Ca 6[Al(OH) 6] 2(CrO 4) 3·26H 2O, the chromate analog of ettringite; 5–75°C

Ca 6[Al(OH) 6] 2(CrO 4) 3·26H 2O, the chromate analog of the sulfate mineral ettringite, was synthesized and characterized by X-ray diffraction, Fourier transform infra-red spectroscopy, thermogravimetric analyses, energy dispersive X-ray spectrometry, and bulk chemical analyses. The solubility of the synthesized solid was measured in a series of dissolution and precipitation experiments conducted at 5–75°C and at initial pH values between 10.5 and 12.5. The ion activity product (IAP) for the reaction Ca 6[Al(OH) 6] 2(CrO 4) 3·26H 2O⇌6Ca 2++2Al(OH) − 4+3CrO 2− 4+4OH −+26H 2O varies with pH unless a CaCrO 4(aq) complex is included in the speciation model. The log K for the formation of this complex by the reaction Ca 2++CrO 2− 4=CaCrO 4(aq) was obtained by minimizing the variance in the IAP for Ca 6[Al(OH) 6] 2(CrO 4) 3·26H 2O. There is no significant trend in the formation constant with temperature and the average log K is 2.77±0.16 over the temperature range 5–75°C. The log solubility product (log K SP) of Ca 6[Al(OH) 6] 2(CrO 4) 3·26H 2O at 25°C is −41.46±0.30. The temperature dependence of the log K SP is log K SP= A− B/ T+ D log( T) where A=498.94±48.99, B=27,499±2257, and D=−181.11±16.74. The values of Δ G 0 r,298 and Δ H 0 r,298 for the dissolution reaction are 236.6±3.9 and 77.5±2.4 kJ mol −1. the values of Δ C 0 P,r,298 and Δ S 0 r,298 are −1506±140 and −534±83 J mol −1 K −1. Using these values and published standard state partial molal quantities for constituent ions, Δ G 0 f,298 =−15,131±19 kJ mol −1, Δ H 0 f,298 =−17,330±8.6 kJ mol −1, Δ S 0 298=2.19±0.10 kJ mol −1 K −1, and Δ C 0 P f,298 =2.12±0.53 kJ mol −1 K −1, were calculated.