title: Selective pharmacophore design for alpha1-adrenoceptor subtypes.
abstract: Alpha1-adrenoceptors are G-protein coupled receptors found in a variety of vascular tissues and responsible for vasoconstriction. Selectivity for each of the three subtypes is an important consideration in drug design in order to minimise the possibility of side effects. Using Catalyst we developed ligand-based pharmacophores from alpha(1a,b,d)-selective antagonists available in the literature using three separate training sets. Four-feature pharmacophores were developed for the alpha(1a) and alpha(1b) subtype-selective antagonists and a five-feature pharmacophore was developed for the alpha(1d) subtype-selective antagonists. The alpha(1a) pharmacophore represents both class I and II compounds with good predictivity for other compounds outside the training set as well. The alpha(1b) pharmacophore best predicts the activity of prazosin analogues as these make up the majority of alpha(1b)-selective antagonists. Unexpectedly, no positive ionisable feature was incorporated in the alpha(1b) pharmacophore. The alpha(1d) pharmacophore was based primarily on one structural class of compounds, but has good predictivity for a heterogeneous test set. Preliminary docking studies using AutoDock and optimised alpha1-adrenoceptor homology models, conducted with the antagonists prazosin (32) and 66, showed good agreement with the findings from the pharmacophores.
authors.affiliation: School of Environmental and Life Sciences, The University of Newcastle, Australia.
authors.forename: Iain J A
authors.initials: IJ
authors.lastname: MacDougall
authors.forename: Renate
authors.initials: R
authors.lastname: Griffith
mesh_terms: D058668:Adrenergic alpha-1 Receptor Antagonists; D000317:Adrenergic alpha-Antagonists / Q000737:chemistry*; D000595:Amino Acid Sequence; D003198:Computer Simulation; D015195:Drug Design; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011487:Protein Conformation; D018340:Receptors, Adrenergic, alpha-1 / Q000737:chemistry*; D012984:Software
chemical_list: D058668:Adrenergic alpha-1 Receptor Antagonists; D000317:Adrenergic alpha-Antagonists; D018340:Receptors, Adrenergic, alpha-1