4.6 Article

VirtualToxLab - A platform for estimating the toxic potential of drugs, chemicals and natural products

Journal

TOXICOLOGY AND APPLIED PHARMACOLOGY
Volume 261, Issue 2, Pages 142-153

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.taap.2012.03.018

Keywords

VirtualToxLab; In silico toxicology; Toxicity alerts; Automated, flexible docking; Multi-dimensional QSAR; Open-access platform

Funding

  1. Swiss National Science Foundation
  2. Jacques en Dolly Gazan Foundation, Zug/Switzerland

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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 proteins, known or suspected to trigger adverse effects. The toxic potential, a non-linear function ranging from 0.0 (none) to 1.0 (extreme), is derived from the individual binding affinities of a compound towards currently 16 target proteins: 10 nuclear receptors (androgen, estrogen alpha, estrogen beta, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor gamma, progesterone, thyroid alpha, and thyroid beta), four members of the cytochrome P450 enzyme family (1A2, 2C9, 206, and 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The interface to the technology allows building and uploading molecular structures, viewing and downloading results and, most importantly, 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. The VirtualToxLab has been used to predict the toxic potential for over 2500 compounds: the results are posted on http://www.virtualtoxlab.org. The free platform - the OpenVirtualToxLab - is accessible (in client-server mode) over the Internet It is free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations. (C) 2012 Elsevier Inc. All rights reserved.

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