Literature DB >> 17125213

3D QSAR selectivity analyses of carbonic anhydrase inhibitors: insights for the design of isozyme selective inhibitors.

Alexander Weber1, Markus Böhm, Claudiu T Supuran, Andrea Scozzafava, Christoph A Sotriffer, Gerhard Klebe.   

Abstract

A 3D QSAR selectivity analysis of carbonic anhydrase (CA) inhibitors using a data set of 87 CA inhibitors is reported. After ligand minimization in the binding pockets of CA I, CA II, and CA IV isoforms, selectivity CoMFA and CoMSIA 3D QSAR models have been derived by taking the affinity differences (DeltapKi) with respect to two CA isozymes as independent variables. Evaluation of the developed 3D QSAR selectivity models allows us to determine amino acids in the respective CA isozymes that possibly play a crucial role for selective inhibition of these isozymes. We further combined the ligand-based 3D QSAR models with the docking program AUTODOCK in order to screen for novel CA inhibitors. Correct binding modes are predicted for various CA inhibitors with respect to known crystal structures. Furthermore, in combination with the developed 3D QSAR models we could successfully estimate the affinity of CA inhibitors even in cases where the applied scoring function failed. This novel strategy to combine AUTODOCK poses with CoMFA/CoMSIA 3D QSAR models can be used as a guideline to assess the relevance of generated binding modes and to accurately predict the binding affinity of newly designed CA inhibitors that could play a crucial role in the treatment of pathologies such as tumors, obesity, or glaucoma.

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Year:  2006        PMID: 17125213     DOI: 10.1021/ci600298r

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  2 in total

1.  Challenging the gold standard for 3D-QSAR: template CoMFA versus X-ray alignment.

Authors:  Bernd Wendt; Richard D Cramer
Journal:  J Comput Aided Mol Des       Date:  2014-06-17       Impact factor: 3.686

2.  Scaffold Hunter: a comprehensive visual analytics framework for drug discovery.

Authors:  Till Schäfer; Nils Kriege; Lina Humbeck; Karsten Klein; Oliver Koch; Petra Mutzel
Journal:  J Cheminform       Date:  2017-05-11       Impact factor: 5.514

  2 in total

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