Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/5202
Title: A genetic-function-approximation-based QSAR model for the affinity of arylpiperazines toward a1 adrenoceptors
Authors: Maccari, L.
Magnani, M.
Strappaghetti, G.
Corelli, Federico 
Botta, Maurizio 
Manetti, Fabrizio 
Issue Date: 2006
Project: None 
Journal: JOURNAL OF CHEMICAL INFORMATION AND MODELING
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 α1 adrenoceptor (α1-AR). The number of rotatable bonds, the hydrogen-bond properties, and a variable belonging to a topological family of descriptors (χ) showed significant roles in the binding process toward α1-AR. The new model was also compared to a previous pharmacophore for α1-AR antagonists and a QSAR model for α2-AR antagonists with the aim of finding common or different key determinants influencing both affinity and selectivity toward α1- and α2-AR.
Description: 
36791
URI: http://hdl.handle.net/20.500.12779/5202
ISSN: 1549-9596
DOI: 10.1021/ci060031z
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