Literature DB >> 9464369

Quantitative analysis of the structural requirements for blockade of the N-methyl-D-aspartate receptor at the phencyclidine binding site.

R T Kroemer1, E Koutsilieri, P Hecht, K R Liedl, P Riederer, J Kornhuber.   

Abstract

Blockade of the N-methyl-D-aspartate receptor by uncompetitive antagonists has implications for symptomatic and neuroprotective therapy of various neuropsychiatric diseases. Since the three-dimensional (3D) structure of this ion channel is unknown, the structural requirements for uncompetitive inhibition were investigated by application of a three-step strategy: At first, Ki values were measured for a number of structurally diverse compounds at the phencyclidine (PCP) binding site in postmortem human frontal cortex. Second, a pharmacophore model was developed for this set of molecules employing a mathematical method called graph theory. The resulting pharmacophore provided a very good explanation for the ability of structurally diverse compounds to bind to the same binding site. Using the experimental data and the pharmacophore as a basis for the third step, a three-dimensional quantitative structure-activity relationship (3D-QSAR) applying comparative molecular field analysis (CoMFA) was performed. The QSAR proved to be highly consistent and showed good predictiveness for several additional molecules. The results give a deeper insight into the structural requirements for effective NMDA receptor antagonism and offer the opportunity for improved drug design. The study represents the first quantitative 3D-QSAR model for NMDA receptor blockade, and it comprises structurally very different molecules. That the alignment for a highly consistent CoMFA is based on an automated 3D pharmacophore analysis has important methodological implications.

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Year:  1998        PMID: 9464369     DOI: 10.1021/jm9704412

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  7 in total

1.  3D-model of the ion channel of NMDA receptor: qualitative and quantitative modeling of the blocker binding.

Authors:  I G Tikhonova; I I Baskin; V A Palyulin; N S Zefirov
Journal:  Dokl Biochem Biophys       Date:  2004 May-Jun       Impact factor: 0.788

2.  Differential binding properties of [3H]dextrorphan and [3H]MK-801 in heterologously expressed NMDA receptors.

Authors:  K T LePage; J E Ishmael; C M Low; S F Traynelis; T F Murray
Journal:  Neuropharmacology       Date:  2005-04-01       Impact factor: 5.250

3.  Preliminary pharmacological evaluation of enantiomeric morphinans.

Authors:  Anna W Sromek; Brian A Provencher; Shayla Russell; Elena Chartoff; Brian I Knapp; Jean M Bidlack; John L Neumeyer
Journal:  ACS Chem Neurosci       Date:  2014-01-08       Impact factor: 4.418

4.  Structural determinants of P-glycoprotein-mediated transport of glucocorticoids.

Authors:  Charles R Yates; Cheng Chang; Jeffrey D Kearbey; Kazuto Yasuda; Erin G Schuetz; Duane D Miller; James T Dalton; Peter W Swaan
Journal:  Pharm Res       Date:  2003-11       Impact factor: 4.200

5.  Structural Analysis, Molecular Modelling and Preliminary Competition Binding Studies of AM-DAN as a NMDA Receptor PCP-Site Fluorescent Ligand.

Authors:  Sethu Ndzibongwana; Samukelo Ngobese; Ahmad Sayed; Ciniso Shongwe; Simon White-Phillips; Jacques Joubert
Journal:  Molecules       Date:  2019-11-13       Impact factor: 4.411

6.  Dual action of amitriptyline on NMDA receptors: enhancement of Ca-dependent desensitization and trapping channel block.

Authors:  Yulia D Stepanenko; Sergei I Boikov; Dmitry A Sibarov; Polina A Abushik; Nina P Vanchakova; Daria Belinskaia; Natalia N Shestakova; Sergei M Antonov
Journal:  Sci Rep       Date:  2019-12-19       Impact factor: 4.379

7.  AlzPlatform: an Alzheimer's disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research.

Authors:  Haibin Liu; Lirong Wang; Mingliang Lv; Rongrong Pei; Peibo Li; Zhong Pei; Yonggang Wang; Weiwei Su; Xiang-Qun Xie
Journal:  J Chem Inf Model       Date:  2014-03-20       Impact factor: 4.956

  7 in total

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