Performance of Kier-Hall E-state descriptors in quantitative structure activity relationship (QSAR) studies of multifunctional molecules.

Performance of the E-state descriptors was tested against simple counts of the 35 atom types that the Kier-Hall E-states are based upon, by building PLS models for clogP, aqueous solubility, human intestinal absorption (HIA) and blood brain barrier (BBB). The results indicate that the simple counts work at least as well as E-state descriptors in building models for solubility and BBB, while surprisingly, simple counts have outperformed E-states by 18% and 30%, respectively, when building the models for HIA and clogP.

Modeling aqueous solubility.

This paper describes the development of an aqueous solubility model based on solubility data from the Syracuse database, calculated octanol-water partition coefficient, and 51 2D molecular descriptors. Two different statistical packages, SIMCA and Cubist, were used and the results were compared. The Cubist model, which comprises a collection of rules, each of which has an associated Multiple Linear Regression model (MLR), gave better overall results on a test set of 640 compounds with an overall squared correlation coefficient of 0.

Predicting ADME properties in silico: methods and models.

Unfavourable absorption, distribution, metabolism and elimination (ADME) properties have been identified as a major cause of failure for candidate molecules in drug development. Consequently, there is increasing interest in the early prediction of ADME properties, with the objective of increasing the success rate of compounds reaching development. This review explores in silico approaches and selected published models for predicting ADME properties from chemical structure alone.

A rapid and facile method for the dereplication of purified natural products.

A new approach to the use of commercial databases for the dereplication of purified natural products has been developed. This is based on searching a text file that links each structure with its molecular weight and an exact count of the number of methyl, methylene, and methine groups it contains. Analysis of such a text file, constructed from a database containing more than 126,000 natural product structures, revealed that these data, readily measured using MS and NMR spectroscopy, are highly discriminating.

Correlation and prediction of a large blood-brain distribution data set--an LFER study.

We report linear free energy relation (LFER) models of the equilibrium distribution of molecules between blood and brain, as log BB values. This method relates log BB values to fundamental molecular properties, such as hydrogen bonding capability, polarity/polarisability and size. Our best model of this form covers 148 compounds, the largest set of log BB data yet used in such a model, resulting in R(2)=0.