In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL QSAR software

Quantitative structure–activity relationship (QSAR) software offers a rapid, cost effective means of prioritizing the mutagenic potential of chemicals. MDL QSAR models were developed using atom-type E-state indices and non-parametric discriminant analysis. Models were developed for Salmonella typhim...

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Veröffentlicht in:	Regulatory toxicology and pharmacology 2005-12, Vol.43 (3), p.313-323
Hauptverfasser:	Contrera, Joseph F., Matthews, Edwin J., Kruhlak, Naomi L., Benz, R. Daniel
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bacillus subtilis Bacteria - drug effects Bacteria - genetics Computer Simulation Databases, Genetic Drug development E-state indices Electrotopological Escherichia coli Escherichia coli - drug effects Escherichia coli - genetics In silico screening Models, Statistical Mutagenicity Mutagenicity Tests Predictive toxicology QSAR Quantitative Structure-Activity Relationship Reproducibility of Results Salmonella Salmonella typhimurium Salmonella typhimurium - drug effects Salmonella typhimurium - genetics Setubal principles Software United States United States Environmental Protection Agency United States Food and Drug Administration
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