Literature DB >> 9522475

Comparison of benzodiazepine-like compounds using topological analysis and genetic algorithms.

N Meurice1, L Leherte, D P Vercauteren.   

Abstract

Four compounds within a set of ligands for the benzodiazepine receptors are characterized by their electron density maps at different resolution levels and reconstructed from calculated structure factors. The resulting complex three-dimensional density maps are first simplified into connected graphs using topological analysis. Then, an original genetic algorithm method, GAGS (Genetic Algorithm for Graph Similarity search), is developed and implemented in order to compare the connected graphs. Finally, the analysis of the best solutions of the algorithm are expressed in terms of functional group superimpositions. The GAGS analysis is applied to different resolution levels of the electron density maps and the resulting models are compared in order to assess the influence of the resolution on the resulting pharmacophore models.

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Year:  1998        PMID: 9522475     DOI: 10.1080/10629369808039141

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  3 in total

1.  Influence of conformation on the representation of small flexible molecules at low resolution: alignment of endothiapepsin ligands.

Authors:  Laurence Leherte; Nathalie Meurice; Daniel P Vercauteren
Journal:  J Comput Aided Mol Des       Date:  2005-11-16       Impact factor: 3.686

2.  Evaluating molecular similarity using reduced representations of the electron density.

Authors:  Nathalie Meurice; Gerald M Maggiora; Daniel P Vercauteren
Journal:  J Mol Model       Date:  2005-05-12       Impact factor: 1.810

3.  The superior fault tolerance of artificial neural network training with a fault/noise injection-based genetic algorithm.

Authors:  Feng Su; Peijiang Yuan; Yangzhen Wang; Chen Zhang
Journal:  Protein Cell       Date:  2016-08-09       Impact factor: 14.870

  3 in total

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