Synthesis and structure-activity relationships of a new model of arylpiperazines. 6. Study of the 5-HT1A/alpha(1)-adrenergic receptor affinity by classical Hansch analysis, artificial neural networks, and computational simulation of ligand recognition

A classical quantitative structure-activity relationship (Hansch) study and artificial neural networks (ANNs) have been applied to a training set of 3 2 substituted phenylpiperazines with affinity for 5-HT1A and alpha (1)-adre nergic receptors, to evaluate the structural requirements that are responsi ble for 5-HT1A/alpha (1) selectivity. The resulting models provide a signif icant correlation of electronic, steric, and hydrophobic parameters with th e biological affinities. Although the derived linear Hansch correlations gi ve good statistics and acceptable predictions, the introduction of nonlinea r relationships in the analysis gives more solid models and more accurate p redictions. In the ANN models on the basis of the obtained 3D plots, the 5- HT1A affinity has a nonlinear dependence on F, V-o, V-m, and pi (o), althou gh the nonlinear relationship is not far from a planar one. The alpha (1)-a drenergic receptor affinity has a clear nonlinear dependence on F, V-o, V-m , pi (o), and pi (m). A comparison of both analyses gives an additional und erstanding for 5-HT1A/alpha (1) selectivity: (a) high F values increase the binding affinity for 5-HT1A receptors and decrease the affinity for alpha (1) sites; (b) the hydrophobicity at the meta-position has only influence f or the alpha (1)-adrenergic receptor; (c) the meta-position seems to be imp licated in the 5-HT1A/alpha (1) selectivity. While the 5-HT1A receptor is a ble to accommodate bulky substituents in the region of its active site, the steric requirements of the alpha (1)-adrenergic receptor at this position are more restricted. This information was used for the design of the new li gand EF-7412 (33) (5-HT1A: K-i (exptl) = 27 nM, alpha (1): K-i (exptl) > 10 00 nM; 5-HT1A: K-i (pred) (ANN) = 36 nM, alpha (1): K-i (pred) (ANN) = 2745 nM) which was characterized as an antagonist in vivo in pre- and postsynap tic 5-HT1AR sites. Computational simulations of the complex between EF-7412 (33) and a 3D model of the transmembrane domain of the 5-HT1A receptor all owed us to define the molecular details of the ligand-receptor interaction that includes: (i) the ionic interaction between the protonated amine of th e ligand and Asp 3.32; (ii) the hydrogen bonds between the m-NHSO2Et group of the ligand and Asn 7.39; and the hydrogen bonds between the hydantoin mo iety of the ligand and (iii) Thr 3.37, (iv) Ser 5.42, and (v) Thr 5.43. The se QSAR and ANN results in combination with computational simulations of li gand recognition will be useful for the design of potent selective 5-HT1A l igands.