Literature DB >> 12767161

A 3D QSAR study on a set of dopamine D4 receptor antagonists.

Jonas Boström1, Markus Böhm, Klaus Gundertofte, Gerhard Klebe.   

Abstract

The molecular alignments obtained from a previously reported pharmacophore model have been employed in a three-dimensional quantitative structure-activity relationship (3D QSAR) study, to obtain a more detailed insight into the structure-activity relationships for D(2) and D(4) receptor antagonists. The frequently applied CoMFA method and the related CoMSIA method were used. Statistically significant models have been derived with these two methods, based on a set of 32 structurally diverse D(2) and D(4) receptor antagonists. The CoMSIA and the CoMFA methods produced equally good models expressed in terms of q(2) values. The predictive power of the derived models were demonstrated to be high. Graphical interpretation of the results, provided by the CoMSIA method, brings to light important structural features of the compounds related to either low- or high-affinity D(2) or D(4) antagonism. The results of the 3D QSAR studies indicate that bulky N-substituents decrease D(2) binding, whereas D(4) binding is enhanced. Electrostatically favorable and unfavorable regions exclusive to D(2) receptor binding were identified. Likewise, certain hydrogen-bond acceptors can be used to lower D(2) affinity. These observations may be exploited for the design of novel dopamine D(4) selective antagonists.

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Year:  2003        PMID: 12767161     DOI: 10.1021/ci034004+

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  6 in total

1.  3D-QSAR illusions.

Authors:  Arthur M Doweyko
Journal:  J Comput Aided Mol Des       Date:  2004 Jul-Sep       Impact factor: 3.686

2.  Effect of steric molecular field settings on CoMFA predictivity.

Authors:  Ruchi R Mittal; Ross A McKinnon; Michael J Sorich
Journal:  J Mol Model       Date:  2007-11-24       Impact factor: 1.810

3.  www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices-the Py-CoMFA web application as tool to build models from pre-aligned datasets.

Authors:  Rino Ragno
Journal:  J Comput Aided Mol Des       Date:  2019-10-08       Impact factor: 3.686

4.  Homology modeling, molecular dynamic simulation, and docking based binding site analysis of human dopamine (D4) receptor.

Authors:  Minasadat Khoddami; Hamid Nadri; Alireza Moradi; Amirhossein Sakhteman
Journal:  J Mol Model       Date:  2015-02-04       Impact factor: 1.810

5.  Common pharmacophore identification using frequent clique detection algorithm.

Authors:  Yevgeniy Podolyan; George Karypis
Journal:  J Chem Inf Model       Date:  2009-01       Impact factor: 4.956

Review 6.  Chemical Structure-Biological Activity Models for Pharmacophores' 3D-Interactions.

Authors:  Mihai V Putz; Corina Duda-Seiman; Daniel Duda-Seiman; Ana-Maria Putz; Iulia Alexandrescu; Maria Mernea; Speranta Avram
Journal:  Int J Mol Sci       Date:  2016-07-08       Impact factor: 5.923

  6 in total

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