FREE-WILSON-TYPE ANALYSIS OF NON-ADDITIVE SUBSTITUENT EFFECTS ON THPB DOPAMINE RECEPTOR AFFINITY USING ARTIFICIAL NEURAL NETWORKS

Abstract

Recently published brain dopamine D2 receptor affinity data of 15 tetrahydroprotoberberine (THPB) derivatives acting as dopamine receptor antagonists have been analyzed by two different QSAR techniques. The following main results were obtained by this analysis: In contrast to an unsuccessful Free-Wilson/Fujita-Ban analysis the investigated receptor binding data could be described by a neural network approach using only binary substructural indicator variables. The artificial/computational neural network was able to recognize that the affinity depends significantly on the simultaneous presence or absence of two or more substituents. A 4-D plot demonstrates the non-additivity/-variability of substituent effects on D2 receptor affinity.