Literature DB >> 26205409

Topological sub-structural molecular design (TOPS-MODE): a useful tool to explore key fragments of human A3 adenosine receptor ligands.

Liane Saíz-Urra1, Marta Teijeira2,3, Virginia Rivero-Buceta4,5, Aliuska Morales Helguera6,7, Maria Celeiro4,8, Ma Carmen Terán4,5, Pedro Besada4,5, Fernanda Borges6.   

Abstract

Adenosine regulates tissue function by activating four G-protein-coupled adenosine receptors (ARs). Selective agonists and antagonists for A3 ARs have been investigated for the treatment of a variety of immune disorders, cancer, brain, and heart ischemic conditions. We herein present a QSAR study based on a Topological sub-structural molecular design (TOPS-MODE) approach, intended to predict the A3 ARs of a diverse dataset of 124 (94 training set/ 30 prediction set) adenosine derivatives. The final model showed good fit and predictive capability, displaying 85.1 % of the experimental variance. The TOPS-MODE approach afforded a better understanding and interpretation of the developed model based on the useful information extracted from the analysis of the contribution of different molecular fragments to the affinity.

Entities:  

Keywords:  Fragment contributions; QSAR; TOPS-MODE, Ddrug discovery; adenosine receptor agonist

Mesh:

Substances:

Year:  2015        PMID: 26205409     DOI: 10.1007/s11030-015-9617-z

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  49 in total

1.  Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships.

Authors:  K Hasegawa; K Funatsu
Journal:  SAR QSAR Environ Res       Date:  2000       Impact factor: 3.000

2.  Geometry, topology, and atom-weights assembly descriptors to predicting A1 adenosine receptors agonists.

Authors:  Maykel Pérez González; Carmen Terán; Marta Teijeira; Pedro Besada
Journal:  Bioorg Med Chem Lett       Date:  2005-05-16       Impact factor: 2.823

3.  Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52.

Authors:  Tatiana I Netzeva; Andrew Worth; Tom Aldenberg; Romualdo Benigni; Mark T D Cronin; Paolo Gramatica; Joanna S Jaworska; Scott Kahn; Gilles Klopman; Carol A Marchant; Glenn Myatt; Nina Nikolova-Jeliazkova; Grace Y Patlewicz; Roger Perkins; David Roberts; Terry Schultz; David W Stanton; Johannes J M van de Sandt; Weida Tong; Gilman Veith; Chihae Yang
Journal:  Altern Lab Anim       Date:  2005-04       Impact factor: 1.303

4.  BCUT descriptors to predicting affinity toward A3 adenosine receptors.

Authors:  Maykel Pérez González; Carmen Terán; Marta Teijeira; Pedro Besada; Maria J González-Moa
Journal:  Bioorg Med Chem Lett       Date:  2005-08-01       Impact factor: 2.823

5.  Air to lung partition coefficients for volatile organic compounds and blood to lung partition coefficients for volatile organic compounds and drugs.

Authors:  Michael H Abraham; Adam Ibrahim; William E Acree
Journal:  Eur J Med Chem       Date:  2007-04-24       Impact factor: 6.514

6.  A segmented principal component analysis-regression approach to quantitative structure-activity relationship modeling.

Authors:  Bahram Hemmateenejad; Maryam Elyasi
Journal:  Anal Chim Acta       Date:  2009-05-09       Impact factor: 6.558

7.  Radial distribution function descriptors: an alternative for predicting A2 A adenosine receptors agonists.

Authors:  Maykel Pérez González; Carmen Terán; Marta Teijeira; Aliuska Morales Helguera
Journal:  Eur J Med Chem       Date:  2005-10-25       Impact factor: 6.514

Review 8.  Medicinal chemistry of adenosine A3 receptor ligands.

Authors:  Christa E Müller
Journal:  Curr Top Med Chem       Date:  2003       Impact factor: 3.295

9.  The A3 adenosine receptor is highly expressed in tumor versus normal cells: potential target for tumor growth inhibition.

Authors:  Lea Madi; Avivit Ochaion; Lea Rath-Wolfson; Sara Bar-Yehuda; Abigail Erlanger; Gil Ohana; Arie Harish; Ofer Merimski; Faina Barer; Pnina Fishman
Journal:  Clin Cancer Res       Date:  2004-07-01       Impact factor: 12.531

10.  From knowledge generation to knowledge archive. A general strategy using TOPS-MODE with DEREK to formulate new alerts for skin sensitization.

Authors:  Ernesto Estrada; Grace Patlewicz; Yaquelin Gutierrez
Journal:  J Chem Inf Comput Sci       Date:  2004 Mar-Apr
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