Document Report Card

ID: ALA1131143

Journal: J Med Chem

Title: Predictive models for GABAA/benzodiazepine receptor subtypes: studies of quantitative structure-activity relationships for imidazobenzodiazepines at five recombinant GABAA/benzodiazepine receptor subtypes [alphaxbeta3gamma2 (x = 1-3, 5, and 6)] via comparative molecular field analysis.

Authors: Huang Q, Liu R, Zhang P, He X, McKernan R, Gan T, Bennett DW, Cook JM.

Abstract: Affinities of a series of substituted imidazobenzodiazepines at recombinant alpha1beta3gamma2, alpha2beta3gamma2, alpha3beta3gamma2, alpha5beta3gamma2, and alpha6beta3gamma2 GABAA/benzodiazepine receptor subtypes are reported. Many of these ligands displayed high affinities (low-nanomolar to subnanomolar scale) at all five receptor subtypes. Furthermore, a number of imidazobenzodiazepines exhibited relatively good selectivity at the alpha5-containing receptor isoform. For example, ligand 27 (RY-023) demonstrated a 55-fold higher selectivity at alpha5beta3gamma2 isoforms in comparison to other receptor subtypes. The affinity ratio of alpha1 (the most prevalent subtype in the brain) to alpha5 of this series of ligands ranged from 60- to 75-fold for the most selective ligands. Studies of quantitative structure-activity relationships (QSAR) by means of comparative molecular field analysis (CoMFA) were carried out. As a result, examination of CoMFA models for all five receptor subtypes demonstrated their predictability for affinities of imidazobenzodiazepines at the five receptor subtypes. Regions of molecular fields which would favor or disfavor the binding affinity of a ligand at a specific receptor subtype were examined via CoMFA for alpha1, alpha2, alpha3, alpha5, and alpha6 subtypes. A CoMFA regression analysis was applied to predict the ratio of Ki alpha1/Ki alpha5, an index for the selectivity of a ligand at the alpha5 subtype. All of the CoMFA models offered good cross-validated correlations for the ligands in the test set as well as the ratios of Ki alpha1/Ki alpha5, which demonstrated their potential for prediction.

CiteXplore: 9767648

DOI: 10.1021/jm980317y