Literature DB >> 19350404

Docking and quantitative structure-activity relationship studies for sulfonyl hydrazides as inhibitors of cytosolic human branched-chain amino acid aminotransferase.

Julio Caballero1, Ariela Vergara-Jaque, Michael Fernández, Deysma Coll.   

Abstract

We have performed the docking of sulfonyl hydrazides complexed with cytosolic branched-chain amino acid aminotransferase (BCATc) to study the orientations and preferred active conformations of these inhibitors. The study was conducted on a selected set of 20 compounds with variation in structure and activity. In addition, the predicted inhibitor concentration (IC(50)) of the sulfonyl hydrazides as BCAT inhibitors were obtained by a quantitative structure-activity relationship (QSAR) method using three-dimensional (3D) vectors. We found that three-dimensional molecule representation of structures based on electron diffraction (3D-MoRSE) scheme contains the most relevant information related to the studied activity. The statistical parameters [cross-validate correlation coefficient (Q(2) = 0.796) and fitted correlation coefficient (R(2) = 0.899)] validated the quality of the 3D-MoRSE predictive model for 16 compounds. Additionally, this model adequately predicted four compounds that were not included in the training set.

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Year:  2009        PMID: 19350404     DOI: 10.1007/s11030-009-9140-1

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


  17 in total

Review 1.  Structure and function of branched chain aminotransferases.

Authors:  S Hutson
Journal:  Prog Nucleic Acid Res Mol Biol       Date:  2001

2.  Identification of mitochondrial branched chain aminotransferase and its isoforms in rat tissues.

Authors:  S M Hutson; R Wallin; T R Hall
Journal:  J Biol Chem       Date:  1992-08-05       Impact factor: 5.157

3.  QSAR studies about cytotoxicity of benzophenazines with dual inhibition toward both topoisomerases I and II: 3D-MoRSE descriptors and statistical considerations about variable selection.

Authors:  Liane Saíz-Urra; Maykel Pérez González; Marta Teijeira
Journal:  Bioorg Med Chem       Date:  2006-09-08       Impact factor: 3.641

4.  Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networks.

Authors:  Julio Caballero; Michael Fernández
Journal:  J Mol Model       Date:  2005-10-21       Impact factor: 1.810

5.  Role of mitochondrial transamination in branched chain amino acid metabolism.

Authors:  S M Hutson; D Fenstermacher; C Mahar
Journal:  J Biol Chem       Date:  1988-03-15       Impact factor: 5.157

6.  Nitrogen shuttling between neurons and glial cells during glutamate synthesis.

Authors:  E Lieth; K F LaNoue; D A Berkich; B Xu; M Ratz; C Taylor; S M Hutson
Journal:  J Neurochem       Date:  2001-03       Impact factor: 5.372

7.  Cellular distribution of branched-chain amino acid aminotransferase isoenzymes among rat brain glial cells in culture.

Authors:  M G Bixel; S M Hutson; B Hamprecht
Journal:  J Histochem Cytochem       Date:  1997-05       Impact factor: 2.479

8.  Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprines.

Authors:  Michael Fernández; Julio Caballero
Journal:  Chem Biol Drug Des       Date:  2006-10       Impact factor: 2.817

9.  Role of branched-chain aminotransferase isoenzymes and gabapentin in neurotransmitter metabolism.

Authors:  S M Hutson; D Berkich; P Drown; B Xu; M Aschner; K F LaNoue
Journal:  J Neurochem       Date:  1998-08       Impact factor: 5.372

10.  Biochemical characterization, homology modeling and docking studies of ornithine delta-aminotransferase--an important enzyme in proline biosynthesis of plants.

Authors:  P Nataraj Sekhar; R Naga Amrutha; Shubhada Sangam; D P S Verma; P B Kavi Kishor
Journal:  J Mol Graph Model       Date:  2007-05-03       Impact factor: 2.518

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  3 in total

1.  Docking and quantitative structure-activity relationship studies for 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline, 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline, and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine derivatives as c-Met kinase inhibitors.

Authors:  Julio Caballero; Miguel Quiliano; Jans H Alzate-Morales; Mirko Zimic; Eric Deharo
Journal:  J Comput Aided Mol Des       Date:  2011-04-13       Impact factor: 3.686

2.  Study of the Differential Activity of Thrombin Inhibitors Using Docking, QSAR, Molecular Dynamics, and MM-GBSA.

Authors:  Karel Mena-Ulecia; William Tiznado; Julio Caballero
Journal:  PLoS One       Date:  2015-11-24       Impact factor: 3.240

3.  Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

Authors:  David Ramírez; Julio Caballero
Journal:  Molecules       Date:  2018-04-28       Impact factor: 4.411

  3 in total

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