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FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes

Šícho, Martin
Autor Šícho, Martin Faculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Center for Bioinformatics , Universität Hamburg , 20146 Hamburg , Germany. Faculty of Chemical Technology, Department of Informatics and Chemistry, CZ-OPENSCREEN: National Infrastructure for Chemical Biology , University of Chemistry and Technology Prague , 166 28 Prague 6 , Czech Republic
Stork, Conrad
Autor Stork, Conrad Faculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Center for Bioinformatics , Universität Hamburg , 20146 Hamburg , Germany
Mazzolari, Angelica
Autor Mazzolari, Angelica Facoltà di Scienze del Farmaco, Dipartimento di Scienze Farmaceutiche "Pietro Pratesi" , Università degli Studi di Milano , I-20133 Milan , Italy
de Bruyn Kops, Christina
Autor de Bruyn Kops, Christina Faculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Center for Bioinformatics , Universität Hamburg , 20146 Hamburg , Germany
Pedretti, Alessandro
Autor Pedretti, Alessandro Facoltà di Scienze del Farmaco, Dipartimento di Scienze Farmaceutiche "Pietro Pratesi" , Università degli Studi di Milano , I-20133 Milan , Italy
Testa, Bernard
Autor Testa, Bernard University of Lausanne , 1015 Lausanne , Switzerland
Vistoli, Giulio
Autor Vistoli, Giulio Facoltà di Scienze del Farmaco, Dipartimento di Scienze Farmaceutiche "Pietro Pratesi" , Università degli Studi di Milano , I-20133 Milan , Italy
Svozil, Daniel, 1971-
Autor Autorita ORCID Faculty of Chemical Technology, Department of Informatics and Chemistry, CZ-OPENSCREEN: National Infrastructure for Chemical Biology , University of Chemistry and Technology Prague , 166 28 Prague 6 , Czech Republic
Kirchmair, Johannes
Autor Kirchmair, Johannes Faculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Center for Bioinformatics , Universität Hamburg , 20146 Hamburg , Germany

Journal of chemical information and modeling. 2019 ; 59 (8) : 3400-3412. [pub] 20190813

J Chem Inf Model
ISSN 1549-960X
Medvik
Zdroj

In this work we present the third generation of FAst MEtabolizer (FAME 3), a collection of extra trees classifiers for the prediction of sites of metabolism (SoMs) in small molecules such as drugs, druglike compounds, natural products, agrochemicals, and cosmetics. FAME 3 was derived from the MetaQSAR database ( Pedretti et al. J. Med. Chem. 2018 , 61 , 1019 ), a recently published data resource on xenobiotic metabolism that contains more than 2100 substrates annotated with more than 6300 experimentally confirmed SoMs related to redox reactions, hydrolysis and other nonredox reactions, and conjugation reactions. In tests with holdout data, FAME 3 models reached competitive performance, with Matthews correlation coefficients (MCCs) ranging from 0.50 for a global model covering phase 1 and phase 2 metabolism, to 0.75 for a focused model for phase 2 metabolism. A model focused on cytochrome P450 metabolism yielded an MCC of 0.57. Results from case studies with several synthetic compounds, natural products, and natural product derivatives demonstrate the agreement between model predictions and literature data even for molecules with structural patterns clearly distinct from those present in the training data. The applicability domains of the individual models were estimated by a new, atom-based distance measure (FAMEscore) that is based on a nearest-neighbor search in the space of atom environments. FAME 3 is available via a public web service at https://nerdd.zbh.uni-hamburg.de/ and as a self-contained Java software package, free for academic and noncommercial research.