Literature DB >> 15762749

Evolutionary chemistry approach toward finding novel inhibitors of the type 2 diabetes target glucose-6-phosphate translocase.

Silke Bräuer1, Michael Almstetter, Walfrido Antuch, Dirk Behnke, Roswitha Taube, Patrick Furer, Sibylle Hess.   

Abstract

A genetic algorithm (GA), driven by experimentally determined biological activities as a feedback fitness function, was used to propose novel small molecules as inhibitors of glucose-6-phosphate translocase (G6PT) in iterative rounds of evolutionary optimization. A straightforward polymer-supported synthetic sequence was implemented to synthesize molecules proposed by the GA, and the biological activities of the compounds were determined by a microsomal assay. Additional compound design strategies were integrated, such as Tanimoto similarity-based selection of starting materials and transfer of favored structure elements into a new chemical scaffold to identify more active and selective inhibitors.

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Year:  2005        PMID: 15762749     DOI: 10.1021/cc049867+

Source DB:  PubMed          Journal:  J Comb Chem        ISSN: 1520-4766


  4 in total

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Authors:  Zhigang Xu; Arthur Y Shaw; Gary S Nichol; Alexandra P Cappelli; Christopher Hulme
Journal:  Mol Divers       Date:  2012-05-24       Impact factor: 2.943

3.  Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm.

Authors:  Stephen D Pickett; Darren V S Green; David L Hunt; David A Pardoe; Ian Hughes
Journal:  ACS Med Chem Lett       Date:  2010-10-20       Impact factor: 4.345

4.  4-(3-Fluoro-4-meth-oxy-phen-yl)-1-(4-meth-oxy-phen-yl)-5-(3,4,5-trimeth-oxy-phen-yl)-1H-imidazole.

Authors:  Xiao-Meng Zhang; Cang Zhang; Wen-Ping Zhang; Xiao-Rong Liu
Journal:  Acta Crystallogr Sect E Struct Rep Online       Date:  2010-11-06
  4 in total

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