The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and analyze metabolic data. This is a plug-in embedded in the VEGA suite of programs (freely downloadable at www.vegazz.net ) and takes advantage from all cheminformatics features implemented in the software with additional tools aimed to perform statistical analyses, similarity searches, and physicochemical profiling of the stored molecules. MetaQSAR also implements a novel metabolism classification, which groups the metabolic reactions in 101 classes and can find numerous applications in metabolic analyses. The potentials of MetaQSAR are here assessed by using it to store and analyze an extended database focused on metabolism of xenobiotics, which was collected by manually curated meta-analysis of the recent literature. The database includes 1890 substrates taken from about 1500 original papers in the years 2004-2015. The database was utilized in both physicochemical analyses and similarity searches, so evidencing the notable potentialities of MetaQSAR, which can find particularly fruitful applications in developing targeted predictive approaches.
MetaQSAR: An Integrated Database Engine to Manage and Analyze Metabolic Data / A. Pedretti, A. Mazzolari, G. Vistoli, B. Testa. - In: JOURNAL OF MEDICINAL CHEMISTRY. - ISSN 0022-2623. - 61:3(2018 Feb 08), pp. 1019-1030.
MetaQSAR: An Integrated Database Engine to Manage and Analyze Metabolic Data
A. Pedretti
;A. Mazzolari;G. Vistoli;
2018
Abstract
The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and analyze metabolic data. This is a plug-in embedded in the VEGA suite of programs (freely downloadable at www.vegazz.net ) and takes advantage from all cheminformatics features implemented in the software with additional tools aimed to perform statistical analyses, similarity searches, and physicochemical profiling of the stored molecules. MetaQSAR also implements a novel metabolism classification, which groups the metabolic reactions in 101 classes and can find numerous applications in metabolic analyses. The potentials of MetaQSAR are here assessed by using it to store and analyze an extended database focused on metabolism of xenobiotics, which was collected by manually curated meta-analysis of the recent literature. The database includes 1890 substrates taken from about 1500 original papers in the years 2004-2015. The database was utilized in both physicochemical analyses and similarity searches, so evidencing the notable potentialities of MetaQSAR, which can find particularly fruitful applications in developing targeted predictive approaches.File | Dimensione | Formato | |
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