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Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...
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OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data.

Angelo Vedani1, Max Dobler2, Zhenquan Hu3

  • 1Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland; Foundation Biographics Laboratory 3R, Klingelbergstrasse 50, 4056 Basel, Switzerland.

Toxicology Letters
|September 22, 2014
PubMed
Summary
This summary is machine-generated.

VirtualToxLab offers in silico toxic potential estimation for drugs and chemicals by simulating small molecule binding to 16 key proteins. This computational tool aids in predicting endocrine disruption, carcinogenicity, and cardiotoxicity, providing atomic-level insights for safety assessments.

Keywords:
3D simulationsIn silico toxicologyMechanistic interpretationOpen-access platformProtein-mediated adverse effects

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Area of Science:

  • Computational toxicology
  • In silico drug discovery
  • Predictive toxicology

Background:

  • Assessing the toxic potential of drugs, chemicals, and natural products is crucial for safety.
  • Existing methods often involve time-consuming and expensive in vivo or in vitro assays.
  • Predictive computational models can accelerate early-stage safety evaluations.

Purpose of the Study:

  • To introduce VirtualToxLab, an in silico technology for estimating toxic potential.
  • To detail the automated protocol simulating and quantifying small molecule binding to key proteins.
  • To enable rationalization of predictions through real-time 3D analysis of binding modes.

Main Methods:

  • Utilizes an automated protocol to simulate and quantify small molecule binding to 16 proteins (10 nuclear receptors, 4 cytochrome P450 enzymes, aryl hydrocarbon receptor, hERG channel).
  • Employs a client-server model on a Linux cluster for computationally demanding simulations.
  • Features a graphical user interface for molecular structure input, result inspection, and 3D binding mode analysis.

Main Results:

  • VirtualToxLab estimates toxic potential, including endocrine and metabolic disruption, carcinogenicity, and cardiotoxicity, based on computed binding affinities.
  • The technology provides atomic-level rationalization of predictions by visualizing compound-protein interactions.
  • Simulations are executed on a high-performance computing cluster.

Conclusions:

  • VirtualToxLab provides a powerful in silico approach for predicting the toxic potential of various compounds.
  • The technology facilitates early-stage safety assessments and aids in understanding mechanisms of toxicity.
  • Free access is available for academic, governmental, and non-profit organizations, promoting wider adoption in research and regulation.