Literature DB >> 12653534

Pharmacophore modeling as an efficient tool in the discovery of novel noncompetitive AMPA receptor antagonists.

Maria Letizia Barreca1, Rosaria Gitto, Silvana Quartarone, Laura De Luca, Giovambattista De Sarro, Alba Chimirri.   

Abstract

A three-dimensional pharmacophore model for the binding of noncompetitive AMPA receptor antagonists was developed in order to map common structural features of highly active compounds. This hypothesis, which consists of two hydrophobic regions, one hydrogen bond acceptor and one aromatic region, was successfully used as framework for the design of a new class of allosteric modulators containing a tetrahydroisoquinoline skeleton and for in silico screening. The promising biological results suggested that the identified molecules might be useful "lead compounds" for future drug development.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12653534     DOI: 10.1021/ci025625q

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


  5 in total

1.  In silico work flow for scaffold hopping in Leishmania.

Authors:  Barnali Waugh; Ambarnil Ghosh; Dhananjay Bhattacharyya; Nanda Ghoshal; Rahul Banerjee
Journal:  BMC Res Notes       Date:  2014-11-17

Review 2.  In Silico Studies in Drug Research Against Neurodegenerative Diseases.

Authors:  Farahnaz Rezaei Makhouri; Jahan B Ghasemi
Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

3.  Characterization of beta3-adrenergic receptor: determination of pharmacophore and 3D QSAR model for beta3 adrenergic receptor agonism.

Authors:  Philip Prathipati; Anil K Saxena
Journal:  J Comput Aided Mol Des       Date:  2005-02       Impact factor: 3.686

4.  Radiosynthesis and preliminary PET evaluation of (18)F-labeled 2-(1-(3-fluorophenyl)-2-oxo-5-(pyrimidin-2-yl)-1,2-dihydropyridin-3-yl)benzonitrile for imaging AMPA receptors.

Authors:  Gengyang Yuan; Graham B Jones; Neil Vasdev; Steven H Liang
Journal:  Bioorg Med Chem Lett       Date:  2016-08-09       Impact factor: 2.823

Review 5.  In silico pharmacology for drug discovery: applications to targets and beyond.

Authors:  S Ekins; J Mestres; B Testa
Journal:  Br J Pharmacol       Date:  2007-06-04       Impact factor: 8.739

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.