Linear free energy relationship analysis of permeability across polydimethylsiloxane (PDMS) membranes and comparison with human skin permeation in vitro

Predicting biophysical properties of small molecules from chromatographic measurements and the solvation parameter model

Biopartitioning processes are challenging to study and often require the sacrifice of multiple animals. Therefore, it is more practical and cost-effective to correlate these processes with easily determined properties, such as chromatographic retention data, or to make predictions based on structural descriptors such as quantitative structure-property relationships or linear free energy relationships. Abraham's solvation parameter model uses six solute properties to characterize the interactions responsible for the transfer of neutral compounds between immiscible phases in chromatographic or biological systems. This review discusses the prediction of biological properties of small molecules from chromatographic measurements and the solvation parameter model. It covers the characteristics of solute descriptors in the solvation parameter model, as well as experimental approaches for their determination. Additionally, it explores recent applications of the solvation parameter model in characterizing biological systems and its use in identifying surrogate chromatographic models for predicting biological properties.

Recent advances for estimating environmental properties for small molecules from chromatographic measurements and the solvation parameter model

The transfer of neutral compounds between immiscible phases in chromatographic or environmental systems can be described by six solute properties (solute descriptors) using the solvation parameter model. The solute descriptors are size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. V and E for liquids are accessible by calculation but the other descriptors and E for solids are determined experimentally by chromatographic, liquid-liquid partition, and solubility measurements. These solute descriptors are available for several thousand compounds in the Abraham solute descriptor databases and for several hundred compounds in the WSU experimental solute descriptor database. In the first part of this review, we highlight features important in defining each descriptor, their experimental determination, compare descriptor quality for the two organized descriptor databases, and methods for estimating Abraham solute descriptors. In the second part we focus on recent applications of the solvation parameter model to characterize environmental systems and its use for the identification of surrogate chromatographic models for estimating environmental properties.

A general linear free energy relationship for predicting partition coefficients of neutral organic compounds

Predicting the effects of organic compounds on environments and biological systems is an important objective for environmental chemistry and human health. The logarithm (to base 10) of the n-octanoll-water partition coefficient has been widely used to predict the mentioned properties. However, the suitability of this parameter for the purpose has been questioned, since the environments relating to the properties may be quite different from that of bulk n-octanol. In this study, we used a theoretical derivation approach to develop a model for predicting the partition coefficients of solutes between water and an organic solvent that may be similar to n-octanol or quite different from it. Our model relies on solute descriptors that can be calculated based on solute structures. It was used to predict the n-octanoll-water, hexadecanel-water and chloroforml-water partition coefficients of solutes. The calculated values of the examined parameters agreed well with their experimental counterparts. The model can find application in the accurate prediction of the effects of organic compounds on environments and the physicochemical properties of organic compounds by a full in-silico approach and can provide useful guidance for improving some properties of organic compounds.