BINDING OF ARYLPIPERAZINES, (ARYLOXY)PROPANOLAMINES, AND TETRAHYDROPYRIDYLINLDOLES TO THE 5-HT1A RECEPTOR - CONTRIBUTION OF THE MOLECULAR LIPOPHILICITY POTENTIAL TO 3-DIMENSIONAL QUANTITATIVE STRUCTURE-AFFINITY RELATIONSHIP MODELS

Citation
P. Gaillard et al., BINDING OF ARYLPIPERAZINES, (ARYLOXY)PROPANOLAMINES, AND TETRAHYDROPYRIDYLINLDOLES TO THE 5-HT1A RECEPTOR - CONTRIBUTION OF THE MOLECULAR LIPOPHILICITY POTENTIAL TO 3-DIMENSIONAL QUANTITATIVE STRUCTURE-AFFINITY RELATIONSHIP MODELS, Journal of medicinal chemistry, 39(1), 1996, pp. 126-134
Citations number
42
Categorie Soggetti
Chemistry Medicinal
ISSN journal
00222623
Volume
39
Issue
1
Year of publication
1996
Pages
126 - 134
Database
ISI
SICI code
0022-2623(1996)39:1<126:BOA(AT>2.0.ZU;2-L
Abstract
A set of 280 5-HT1A receptor Ligands were selected from available lite rature data according to predefined criteria and subjected to three-di mensional quantitative structure-affinity relationship analysis using comparative molecular field analysis. No model was obtained for seroto nin analogues (19 compounds) and aminotetralins (60 compounds), despit e a variety of alignment hypotheses being tried. In contrast, the ster ic, electrostatic, and lipophilicity fields alone and in combination y ielded informative models for arylpiperazines (101 training compounds and 12 test compounds), (argrloxy)propanolamines (30 training compound s and four test compounds), and tetrahydropyridylindoles (54 training compounds) taken separately (models A, B, and C). Arylpiperazines and (aryloxy)propanolamines were then combined successfully to yield reaso nably good models for 131 compounds (model D). In a last step, the thr ee chemical classes (185 compounds) were combined, again successfully (model E). This stepwise procedure not only ascertains self-consistenc y in alignments but it also allows statistical signals (i.e., favorabl e or unfavorable regions around molecules) to emerge which cannot exis t in a single chemical class. The models so obtained reveal a number o f interaction sites between ligands and the 5-HT1A receptor, and exten d the information gathered from a model based on homology modeling.