title: A genetic-function-approximation-based QSAR model for the affinity of arylpiperazines toward alpha1 adrenoceptors.
abstract: The genetic function approximation (GFA) algorithm has been used to derive a three-term QSAR equation able to correlate the structural properties of arylpiperazine derivatives with their affinity toward the alpha1 adrenoceptor (alpha1-AR). The number of rotatable bonds, the hydrogen-bond properties, and a variable belonging to a topological family of descriptors (chi) showed significant roles in the binding process toward alpha1-AR. The new model was also compared to a previous pharmacophore for alpha1-AR antagonists and a QSAR model for alpha2-AR antagonists with the aim of finding common or different key determinants influencing both affinity and selectivity toward alpha1- and alpha2-AR.
authors.affiliation: Dipartimento Farmaco Chimico Tecnologico, Università degli Studi di Siena, Via Alcide de Gasperi, 2, I-53100 Siena, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Maccari
authors.forename: Matteo
authors.initials: M
authors.lastname: Magnani
authors.forename: Giovannella
authors.initials: G
authors.lastname: Strappaghetti
authors.forename: Federico
authors.initials: F
authors.lastname: Corelli
authors.forename: Maurizio
authors.initials: M
authors.lastname: Botta
authors.forename: Fabrizio
authors.initials: F
authors.lastname: Manetti
mesh_terms: D008958:Models, Molecular; D010879:Piperazines / Q000737:chemistry* / Q000494:pharmacology*; D021281:Quantitative Structure-Activity Relationship; D018340:Receptors, Adrenergic, alpha-1 / Q000187:drug effects*
chemical_list: D010879:Piperazines; D018340:Receptors, Adrenergic, alpha-1