Literature DB >> 27490388

In Silico Predictions of Drug - Drug Interactions Caused by CYP1A2, 2C9 and 3A4 Inhibition - a Comparative Study of Virtual Screening Performance.

Teresa Kaserer1, Martina Höferl2, Klara Müller1, Sebastian Elmer3, Markus Ganzera3, Walter Jäger2, Daniela Schuster4.   

Abstract

The cytochrome P450 (CYP) superfamily represents the major enzyme class responsible for the metabolism of exogenous compounds. Investigation of clearance pathways is therefore an integral part in early drug development, as any alteration of metabolic enzymes may markedly influence the toxicological profile and efficacy of novel compounds. In silico methods are widely applied in drug development to complement experimental approaches. Several different tools are available for that purpose, however, for CYP enzymes they have only been applied retrospectively so far. Within this study, pharmacophore- and shape-based models and a docking protocol were generated for the prediction of CYP1A2, 2C9, and 3A4 inhibition. All theoretically validated models, the validated docking workflow, and additional external bioactivity profiling tools were applied independently and in parallel to predict the CYP inhibition of 29 compounds from synthetic and natural origin. After subsequent experimental assessment of the in silico predictions, we analyzed and compared the prospective performance of all methods, thereby defining the suitability of the applied techniques for CYP enzymes. We observed quite substantial differences in the performances of the applied tools, suggesting that the rational selection of that virtual screening method that proved to perform best can largely improve the success rates when it comes to CYP inhibition prediction.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  2D similarity; Docking; Metabolism; Pharmacophore modeling; Shape-based modeling

Mesh:

Substances:

Year:  2015        PMID: 27490388     DOI: 10.1002/minf.201400192

Source DB:  PubMed          Journal:  Mol Inform        ISSN: 1868-1743            Impact factor:   3.353


  4 in total

Review 1.  Virtual screening applications in short-chain dehydrogenase/reductase research.

Authors:  Katharina R Beck; Teresa Kaserer; Daniela Schuster; Alex Odermatt
Journal:  J Steroid Biochem Mol Biol       Date:  2017-03-09       Impact factor: 4.292

2.  Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation.

Authors:  Alexander Dmitriev; Dmitry Filimonov; Alexey Lagunin; Dmitry Karasev; Pavel Pogodin; Anastasiya Rudik; Vladimir Poroikov
Journal:  Molecules       Date:  2019-10-31       Impact factor: 4.411

Review 3.  Drugs from nature targeting inflammation (DNTI): a successful Austrian interdisciplinary network project.

Authors:  Birgit Waltenberger; Atanas G Atanasov; Elke H Heiss; David Bernhard; Judith M Rollinger; Johannes M Breuss; Daniela Schuster; Rudolf Bauer; Brigitte Kopp; Chlodwig Franz; Valery Bochkov; Marko D Mihovilovic; Verena M Dirsch; Hermann Stuppner
Journal:  Monatsh Chem       Date:  2016-02-25       Impact factor: 1.451

Review 4.  Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases.

Authors:  Teresa Kaserer; Katharina R Beck; Muhammad Akram; Alex Odermatt; Daniela Schuster
Journal:  Molecules       Date:  2015-12-19       Impact factor: 4.411

  4 in total

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