Modeling drug-melanin interaction with theoretical linear solvation energy relationships.

The affinity of drugs and other xenobiotic agents for melanin is a well-known phenomenon, often occurring with serious physiological consequences. For example, the interaction of anti-psychotic drugs with neuromelanin may play a pivotal role in the induction of extrapyramidal movement disorders associated with the chronic administration of phenothiazine and other neuroleptic agents. Little, however, is known about the complete nature of melanin-drug binding and the impact of these interactions on the physico-chemical properties of melanin. Data, such as binding affinities, can be analyzed using recently developed computational methods that combine mathematical models of chemical structure with statistical analysis. In particular, theoretical linear solvation energy relationships provide a convenient model for understanding and predicting biological, chemical, and physical properties. By using this modeling technique, drug-melanin binding of a set of 16 compounds has been analyzed with correlation analysis and a set of theoretical molecular parameters in order to better understand and characterize drug-melanin interactions. The resulting correlation equation supports a charge transfer model for drug-melanin complex formation and can also be used to estimate binding constants for related compounds.

Using theoretical descriptors in quantitative structure-activity relationships: some toxicological indices.

The application of computational techniques to medicinal chemistry is growing at a tremendous rate. Quantitative structure-activity relationships (QSAR), which relate biological and toxicological activities to structural features, have been employed widely to correlate structure to activity. A difficulty of this approach has been nonuniformity of parameter sets and the inability to examine contributions across properties and data sets. Linear solvation energy relationships (LSER) developed by Kamlet and Taft circumvent many of the difficulties and successfully utilize a single set of parameters for a wide range of physical, chemical, and biological properties. We have replaced the LSER solvato-chromatic parameters with theoretically determined parameters to permit better a priori prediction of properties. Comparison of the two parameter sets for five biological activities is presented, showing the excellent fit of the theoretically determined parameters.