Literature DB >> 19576786

Identification, structure-activity relationships and molecular modeling of potent triamine and piperazine opioid ligands.

Austin B Yongye1, Jon R Appel, Marc A Giulianotti, Colette T Dooley, Jose L Medina-Franco, Adel Nefzi, Richard A Houghten, Karina Martínez-Mayorga.   

Abstract

Opioid receptors are important targets for pain management. Here, we report the synthesis and biological evaluation of three positional scanning combinatorial libraries, consisting of linear triamines and piperazines. A highly potent (14 nM) and selective (IC(50(mu))/IC(50(kappa))=71; IC(50(delta))/IC(50(kappa))=714) triamine for the kappa-opioid receptor was found. In addition, non-selective mu-kappa binders were obtained, with binding affinities of 54 nM and 22 nM for mu- and kappa-opioid receptors, respectively. Structure-activity relationships of each subset are described. 3D molecular alignments based on shape similarity to internal and external query molecules were carried out. For the combinatorial chemistry dataset studied here a 1.3 similarity cut-off value was observed to be efficient in the rocs-based alignment method. Interactions from the overlays analyzed in the binding sites of homology models of the receptors revealed specific substitution patterns for enhancing binding affinity in the piperazine series. Pharmacophore modeling of the compounds found from the three combinatorial libraries was also performed. The pharmacophore model indicated that the important feature for receptor binding activity with the mu-receptor was the presence of at least one hydrogen bond acceptor and one aromatic hydrophobic group. Whereas for the kappa-receptor two binding modes emerged with one set of compounds employing the hydrogen bond acceptor and aromatic hydrophobic group, and a second set possibly via interactions with the receptor by hydrophobic and ionic salt-bridges.

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Year:  2009        PMID: 19576786      PMCID: PMC2746904          DOI: 10.1016/j.bmc.2009.06.026

Source DB:  PubMed          Journal:  Bioorg Med Chem        ISSN: 0968-0896            Impact factor:   3.641


  36 in total

Review 1.  Mixture-based synthetic combinatorial libraries.

Authors:  R A Houghten; C Pinilla; J R Appel; S E Blondelle; C T Dooley; J Eichler; A Nefzi; J M Ostresh
Journal:  J Med Chem       Date:  1999-09-23       Impact factor: 7.446

2.  A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes.

Authors:  Jeremy L Jenkins; Meir Glick; John W Davies
Journal:  J Med Chem       Date:  2004-12-02       Impact factor: 7.446

Review 3.  Molecular recognition of opioid receptor ligands.

Authors:  Brian E Kane; Bengt Svensson; David M Ferguson
Journal:  AAPS J       Date:  2006-03-10       Impact factor: 4.009

4.  Comparison of shape-matching and docking as virtual screening tools.

Authors:  Paul C D Hawkins; A Geoffrey Skillman; Anthony Nicholls
Journal:  J Med Chem       Date:  2007-01-11       Impact factor: 7.446

Review 5.  Re-discussion of the importance of ionic interactions in stabilizing ligand-opioid receptor complex and in activating signal transduction.

Authors:  Luca Gentilucci; Federico Squassabia; Roberto Artali
Journal:  Curr Drug Targets       Date:  2007-01       Impact factor: 3.465

6.  A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist.

Authors:  Nidhi Singh; Gwénaël Chevé; David M Ferguson; Christopher R McCurdy
Journal:  J Comput Aided Mol Des       Date:  2006-09-29       Impact factor: 3.686

Review 7.  Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches.

Authors:  Hanna Eckert; Jürgen Bajorath
Journal:  Drug Discov Today       Date:  2007-02-07       Impact factor: 7.851

8.  Strategies for the use of mixture-based synthetic combinatorial libraries: scaffold ranking, direct testing in vivo, and enhanced deconvolution by computational methods.

Authors:  Richard A Houghten; Clemencia Pinilla; Marc A Giulianotti; Jon R Appel; Colette T Dooley; Adel Nefzi; John M Ostresh; Yongping Yu; Gerald M Maggiora; Jose L Medina-Franco; Daniela Brunner; Jeff Schneider
Journal:  J Comb Chem       Date:  2007-12-08

9.  A similarity-based data-fusion approach to the visual characterization and comparison of compound databases.

Authors:  José L Medina-Franco; Gerald M Maggiora; Marc A Giulianotti; Clemencia Pinilla; Richard A Houghten
Journal:  Chem Biol Drug Des       Date:  2007-10-10       Impact factor: 2.817

10.  The use of three-dimensional shape and electrostatic similarity searching in the identification of a melanin-concentrating hormone receptor 1 antagonist.

Authors:  Steven W Muchmore; Andrew J Souers; Irini Akritopoulou-Zanze
Journal:  Chem Biol Drug Des       Date:  2006-02       Impact factor: 2.817

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  3 in total

Review 1.  Comprehensive survey of chemical libraries for drug discovery and chemical biology: 2009.

Authors:  Roland E Dolle; Bertrand Le Bourdonnec; Karin Worm; Guillermo A Morales; Craig J Thomas; Wei Zhang
Journal:  J Comb Chem       Date:  2010-10-05

2.  Integrating computational and mixture-based screening of combinatorial libraries.

Authors:  Austin B Yongye; Clemencia Pinilla; Jose L Medina-Franco; Marc A Giulianotti; Colette T Dooley; Jon R Appel; Adel Nefzi; Thomas Scior; Richard A Houghten; Karina Martínez-Mayorga
Journal:  J Mol Model       Date:  2010-09-21       Impact factor: 1.810

3.  Ligand/kappa-opioid receptor interactions: insights from the X-ray crystal structure.

Authors:  Karina Martinez-Mayorga; Kendall G Byler; Austin B Yongye; Marc A Giulianotti; Colette T Dooley; Richard A Houghten
Journal:  Eur J Med Chem       Date:  2013-05-30       Impact factor: 6.514

  3 in total

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