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.

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.

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.

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.