The Relationship Between Molecular Symmetry and Physicochemical Properties Involving Boiling and Melting of Organic Compounds.

OBJECTIVE AND METHODS: The reliable estimation of phase transition physicochemical properties such as boiling and melting points can be valuable when designing compounds with desired physicochemical properties. This study explores the role of external rotational symmetry in determining boiling and melting points of select organic compounds. Using experimental data from the literature, the entropies of boiling and fusion were obtained for 541 compounds. The statistical significance of external rotational symmetry number on entropies of phase change was determined by using multiple linear regression. In addition, a series of aliphatic hydrocarbons, polysubstituted benzenes, and di-substituted napthalenes are used as examples to demonstrate the role of external symmetry on transition temperature. RESULTS: The results reveal that symmetry is not well correlated with boiling point but is statistically significant in melting point. CONCLUSION: The lack of correlation between the boiling point and the symmetry number reflects the fact that molecules have a high degree of rotational freedom in both the liquid and the vapor. On the other hand, the strong relationship between symmetry and melting point reflects the fact that molecules are rotationally restricted in the crystal but not in the liquid. Since the symmetry number is equal to the number of ways that the molecule can be properly oriented for incorporation into the crystal lattice, it is a significant determinant of the melting point.

Machine learning transition temperatures from 2D structure.

A priori knowledge of physicochemical properties such as melting and boiling could expedite materials discovery. However, theoretical modeling from first principles poses a challenge for efficient virtual screening of potential candidates. As an alternative, the tools of data science are becoming increasingly important for exploring chemical datasets and predicting material properties. Herein, we extend a molecular representation, or set of descriptors, first developed for quantitative structure-property relationship modeling by Yalkowsky and coworkers known as the Unified Physicochemical Property Estimation Relationships (UPPER). This molecular representation has group-constitutive and geometrical descriptors that map to enthalpy and entropy; two thermodynamic quantities that drive thermal phase transitions. We extend the UPPER representation to include additional information about sp2-bonded fragments. Additionally, instead of using the UPPER descriptors in a series of thermodynamically-inspired calculations, as per Yalkowsky, we use the descriptors to construct a vector representation for use with machine learning techniques. The concise and easy-to-compute representation, combined with a gradient-boosting decision tree model, provides an appealing framework for predicting experimental transition temperatures in a diverse chemical space. An application to energetic materials shows that the method is predictive, despite a relatively modest energetics reference dataset. We also report competitive results on diverse public datasets of melting points (i.e., OCHEM, Enamine, Bradley, and Bergström) comprised of over 47k structures. Open source software is available at https://github.com/USArmyResearchLab/ARL-UPPER.

Effect of pH and Ionic Strength on the Solubility of Quinoline: Back-to-Basics.

The interest of quinoline as a contaminant agent and as scaffold for the development of new therapeutic agent warrants to revisit the pH-solubility behavior of quinoline (Q) and quinoline derivatives (Q-derivatives) with possible salting-out effect. Q is a weak base with potential hazard upon exposure that may be occupational by inhalation or ingestion of or dermal exposure to particulates in certain industries; or simply by inhalation of cigarette smoke. In contrast, quinoline and its derivatives are useful in diverse therapeutic applications such as anticancer, antiseptic, antipyretic, antiviral, and antimalarial. These claims have raised the possibility of using quinoline motif for the synthesis of new drugs; however, it may act as a pollutant on soil and water as ionizable organic compounds (IOC). The solubility and partitioning behavior of Q may be a critical factor in determining the extent of inhalation and oral absorption or sorption onto soil and water. Studies on the solubility of Q have been reported; however, due to Q-derivatives distinctive usage, it is necessary to revisit and evaluate the solubility profile of Q at different pH levels and ionic strengths. This study reports a simple analytical method for determining the solubility of nitrogen heterocyclic compounds and possible salting-out effect as a function of pH, buffer concentration, and ionic strength. This information can be of value when developing Q-derivatives and to enhance understanding of Q as well as its derivatives behavior in the gastrointestinal tract or when evaluating the presence of Q as an environmental contaminant.

Comments on prediction of the aqueous solubility using the general solubility equation (GSE) versus a genetic algorithm and a support vector machine model.

The general solubility equation (GSE) is the state-of-the-art method for estimating the aqueous solubilities of organic compounds. It is an extremely simple equation that expresses aqueous solubility as a function of only two inputs: the octanol-water partition coefficient calculated by readily available softwares like clogP and ACD/logP, and the commonly known melting point of the solute. Recently, Bahadori et al. proposed that their genetic algorithm support vector machine is a "better" predictor. This paper compares the use of the of Bahadori et al. model for the prediction of aqueous solubility to the existing GSE model.

Estimating the Physicochemical Properties of Polysubstituted Aromatic Compounds Using UPPER.

The UPPER model (Unified Physicochemical Property Estimation Relationships) has been used to predict 9 essential physicochemical properties of pure compounds. It was developed almost 25 years ago and has been validated by the Yalkowsky group for almost 2000 aliphatic, aromatic, and polyhalogenated hydrocarbons. UPPER is based on a group of additive and nonadditive descriptors along with a series of well-accepted thermodynamic relationships. In this model, the 2-dimensional chemical structure is the only input needed. This work extends the applicability of UPPER to hydrogen bonding and non-hydrogen bonding aromatic compounds with several functional groups such as alcohol, aldehyde, ketone, carboxylic acid, carbonate, carbamate, amine, amide, nitrile as well as aceto, and nitro compounds. The total data set includes almost 3000 compounds. Aside from the enthalpies and entropies of melting and boiling, no training set is used for the calculation of the properties. The results show that UPPER enables a reasonable estimation of all the considered properties.

Overcoming the Challenges of Low Drug Solubility in the Intravenous Formulation of Solithromycin.

Solithromycin is a fluoro-ketolide (a fourth-generation macrolide) antibiotic that has been undergoing clinical trials for the treatment of community-acquired bacterial pneumonia. In this study, development of the tri-amino acid-buffered solithromycin intravenous (IV) formulation was performed to minimize the occurrence of infusion-associated local adverse events (infusion-site pain or phlebitis) observed in patients who received the tartaric acid-buffered IV formulation with a lower buffered capacity during phase I clinical trials. Development of the tri-amino acids-buffered solithromycin IV formulation was achieved using a dynamic in vitro precipitation model. Computational modeling also supports the superiority of the amino acid-buffered formulation over the tartaric aid-buffered formulation.

A rule of unity for human intestinal absorption 3: Application to pharmaceuticals.

The rule of unity is based on a simple absorption parameter, Π, that can accurately predict whether or not an orally administered drug will be well absorbed or poorly absorbed. The intrinsic aqueous solubility and octanol-water partition coefficient, along with the drug dose are used to calculate Π. We show that a single delineator value for Π exist that can distinguish whether a drug is likely to be well absorbed (FA ≥ 0.5) or poorly absorbed (FA < 0.5) at any specified dose. The model is shown to give 82.5% correct predictions for over 938 pharmaceuticals. The maximum well-absorbed dose (i.e. the maximum dose that will be more than 50% absorbed) calculated using this model can be utilized as a guideline for drug design and synthesis.

Estimation of Melting Points of Organics.

Unified physicochemical property estimation relationships is a system of empirical and theoretical relationships that relate 20 physicochemical properties of organic molecules to each other and to chemical structure. Melting point is a key parameter in the unified physicochemical property estimation relationships scheme because it is a determinant of several other properties including vapor pressure, and solubility. This review describes the first-principals calculation of the melting points of organic compounds from structure. The calculation is based on the fact that the melting point, Tm, is equal to the ratio of the heat of melting, ΔHm, to the entropy of melting, ΔSm. The heat of melting is shown to be an additive constitutive property. However, the entropy of melting is not entirely group additive. It is primarily dependent on molecular geometry, including parameters which reflect the degree of restriction of molecular motion in the crystal to that of the liquid. Symmetry, eccentricity, chirality, flexibility, and hydrogen bonding, each affect molecular freedom in different ways and thus make different contributions to the total entropy of fusion. The relationships of these entropy determining parameters to chemical structure are used to develop a reasonably accurate means of predicting the melting points over 2000 compounds.

Imaging of in vitro parenteral drug precipitation.

Solid particulate matter introduced into the bloodstream as a result of parenteral drug administration can produce serious pathological conditions. Particulate matter that cannot be eliminated by pre-infusion filtration is often the result of drug precipitation that occurs when certain parenteral formulations are mixed with blood. A new device is designed to model the mixing of drug formulations with flowing blood utilizing a uniquely designed flow cell and a CCD camera to view the formulation as it is mixed with a blood surrogate in real time. The performance of the proposed device is measured using 3 commercially available parenteral formulations previously tested using a validated in vitro model.

Calculating the Solubilities of Drugs and Drug-Like Compounds in Octanol.

A modification of the Van't Hoff equation is used to predict the solubility of organic compounds in dry octanol. The new equation describes a linear relationship between the logarithm of the solubility of a solute in octanol to its melting temperature. More than 620 experimentally measured octanol solubilities, collected from the literature, are used to validate the equation without using any regression or fitting. The average absolute error of the prediction is 0.66 log units.

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 2. Aqueous solubility, octanol solubility and octanol-water partition coefficient.

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses additive and non-additive parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky (2014) on a data set of 700 hydrocarbons. Recently, Admire et al. (2014) expanded the model to predict the boiling and melting points of 1288 polyhalogenated benzenes, biphenyls, dibenzo-p-dioxins, diphenyl ethers, anisoles and alkanes. In this work, 19 new group descriptors are determined and used to predict the aqueous solubilities, octanol solubilities and the octanol-water coefficients.

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 1. Boiling point and melting point.

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses enthalpic and entropic parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky on a data set of 700 hydrocarbons. The aim of this work is to expand the UPPER model to estimate the boiling and melting points of polyhalogenated compounds. In this work, 19 new group descriptors are defined and used to predict the transition temperatures of an additional 1288 compounds. The boiling points of 808 and the melting points of 742 polyhalogenated compounds are predicted with average absolute errors of 13.56 K and 25.85 K, respectively.

The rule of unity for human intestinal absorption 2: application to pharmaceutical drugs that are marketed as salts.

The efficiency of the human intestinal absorption (HIA) of the 59 drugs which are marketed as salts is predicted using the rule of unity. Intrinsic aqueous solubilities and partition coefficients along with the drug dose are used to calculate modified absorption potential (MAP) values. These values are shown to be related to the fraction of the dose that is absorbed upon oral administration in humans (FA). It is shown that the MAP value can distinguish between drugs that are poorly absorbed (FA <0.5) and those that are well absorbed (FA ≥ 0.5). Inspection of the data as well as a receiver operative characteristic (ROC) plot shows that a single critical MAP value can be used for predicting efficient human absorption of drugs. This forms the basis of a simple rule of unity based solely on in vitro data for predicting whether or not a drug will be well absorbed at a given dose.

Unified physicochemical property estimation relationships (UPPER).

The knowledge of physicochemical properties of organic compounds becomes increasingly important in pharmaceutical sciences, chemical engineering, and other fields. In this study, we developed UPPER (Unified Physicochemical Property Estimation Relationships), a comprehensive model for the estimation of 20 physicochemical properties of organic compounds. UPPER is a system of thermodynamically sound relationships that relate the various phase-transition properties to one another, which includes transition heats, transition entropies, transition temperatures, molar volume, vapor pressure, solubilities and partition coefficients in different solvents, and so on. UPPER integrates group contributions with the molecular geometric factors that affect transition entropies. All of the predictions are directly based on molecular structure. As a result, the proposed model provides a simple and accurate prediction of the properties studied. UPPER is designed to predict industrially, pharmaceutically, and environmentally relevant physicochemical properties. It can be an aid for the efficient design and synthesis of compounds with optimal physicochemical properties.

Carnelley's rule and the prediction of melting point.

Carnelley (1882) made some important and useful observations on the relationship between the arrangement of the atoms in a molecule and its melting point. According to Brown and Brown (2000. J Chem Ed 77:724-731), Carnelley's rule states "of two or more isometric compounds, those whose atoms are the more symmetrically and the more compactly arranged melt higher than those in which the atomic arrangement is asymmetrical or in the form of long chains." Carnelley's rule can best be understood and quantitated from the dependence of the entropy of melting upon molecular geometry.

Predicting the octanol solubility of organic compounds.

The molar octanol solubility of an organic nonelectrolytes can be reasonably predicted solely from its melting point provided that its liquid (or a hypothetical super-cooled liquid) form is miscible with octanol. The aim of this work is to develop criteria to determine if the real or hypothetical liquid form of a given compound will be miscible with octanol based on its molar volume and solubility parameter. Fortunately, most organic compounds (including most drugs) conform to the criteria for complete liquid miscibility, and therefore have solubilities that are proportional to their melting points. The results show that more than 95% of the octanol solubilities studied are predicted with an error of less than 1 logarithmic unit.

Preformulation study of NSC-726796.

A stability-indicating high-performance liquid chromatography method to quantify 2-(2,4-difluorophenyl)-4,5,6,7-tetrafluoroisoindoline-1,3-dione (NSC-726796) and its three main degradation products was developed. This method was used to investigate its degradation kinetics and mechanism. The reaction follows first-order kinetics and appears to be base catalyzed with the maximum stability at pH 1. The products were identified as 2-(2,4-difluorophenylcarbamoyl)-3,4,5,6-tetrafluorobenzoic acid (NSC-749820), 2,4-difluoroaniline, and tetrafluorophthalic acid. The parent drug, NSC-726796, was also found to react with methanol and ethanol. NSC-726796 demonstrates antiangiogenic activity, however, when its degradant NSC749820 does not show antiangiogenic activity.

Perspective on improving passive human intestinal absorption.

Methods such as pH adjustment, cosolvency, complexation, and micellization are routinely used to increase the concentration of dissolved drug in the gastrointestinal (GI) lumen over that of a saturated solution. However, these solubilizing agents also reduce the membrane-water distribution coefficient so that the membrane transport rate is not changed. Also, dilution of a formulation upon administration results in: (1) a pH change toward that of the GI fluid, (2) an exponential decrease in cosolvency, and (3) disassociation of complexes and the disintegration of micelles. As a result, these solubilizing agents cannot be expected to produce any increase in membrane transport-limited drug absorption over that of a suspension of unformulated drug.

Stability of 5-fluoro-2'-deoxycytidine and tetrahydrouridine in combination.

In vivo, the DNA methyltransferase inhibitor, 5-fluoro-2'-deoxycytidine (FdCyd, NSC-48006), is rapidly converted to its unwanted metabolites. Tetrahydrouridine (THU, NSC-112907), a cytidine deaminase inhibitor can block the first metabolic step in FdCyd catabolism. Clinical studies have shown that co-administration with THU can inhibit the metabolism of FdCyd. The National Cancer Institute is particularly interested in a 1:5 FdCyd/THU formulation. The purpose of this study was to investigate the in vitro pH stability of FdCyd and THU individually and in combination. A stability-indicating high-performance liquid chromatography method for the quantification of both compounds and their degradants was developed using a ZIC(R)-HILIC column. The effect of THU and FdCyd on the in vitro degradation of each other was studied as a function of pH from 1.0 to 7.4 in aqueous solutions at 37 degrees C. The degradation of FdCyd appears to be first-order and acid-catalyzed. THU equilibrates with at least one of its degradants. The combination of FdCyd and THU in solution does not affect the stability of either compound. The stability and compatibility of FdCyd and THU in the solid state at increased relative humidity and at various temperatures are also evaluated.

Estimation of the ideal solubility (crystal-liquid fugacity ratio) of organic compounds.

Melting point, entropy of melting and heat capacity of melting are required for the calculation of the ideal solubility of a solid solute via the Clausius-Clapyron equation. This article reviews the published approximations of estimating entropy and heat capacity of melting. By comparing the available experimental results to calculated values the authors attempt to identify the best estimation of the ideal solubility and crystal-liquid fugacity ratio for organic compounds.