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OpenVirtualToxLab - a platform for generating and exchanging in silico toxicity data

Vedani, Angelo and Dobler, Max and Hu, Zhenquan and Smiesko, Martin. (2014) OpenVirtualToxLab - a platform for generating and exchanging in silico toxicity data. Toxicology letters, Vol. 232, H. 2. pp. 519-532.

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Official URL: http://edoc.unibas.ch/dok/A6329098

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Abstract

The VirtualToxLab is an in silico technology for estimating the toxic potential - endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity - of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The toxic potential of a compound - its ability to trigger adverse effects - is derived from its computed binding affinities toward these very proteins: The computationally demanding simulations are executed in client-server mode on a Linux cluster of the University of Basel. The graphical-user interface supports all computer platforms, allows building and uploading molecular structures, inspecting and downloading the results and, most important, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. Access to the VirtualToxLab is available free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations.
Faculties and Departments:05 Faculty of Science > Departement Pharmazeutische Wissenschaften > Ehemalige Einheiten Pharmazie > Molecular Modeling (Vedani)
UniBasel Contributors:Vedani, Angelo and Smiesko, Martin and Hu, Zhenquan
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:Elsevier
ISSN:0378-4274
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:06 Feb 2015 09:58
Deposited On:06 Feb 2015 09:58

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