VirtualToxLab - in silico prediction of the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. Two years and 2,000 compounds of experience: a progress report.
The VirtualToxLab is an in silico tool for predicting the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. It is based on a fully automated protocol and calculates the binding affinity of any molecule of interest towards a series of 12 proteins, known or suspected to trigger adverse effects and estimates the resulting toxic potential. In contrast to other approaches in the field, the technology allows to rationalize a prediction at the molecular level by interactively analyzing the binding mode of the tested compound with any target protein in 3D. The technology is accessible over the Internet (via a secure SSH protocol) and available for any science-oriented organization. The toxic potential - a complex value derived from the individual binding affinities, their standard deviation and the quality of the underlying model (number and ratio of training and test compounds, activity range covered) - of existing and hypothetical compounds is estimated by simulating and quantifying their interactions towards a series of macromolecular targets at the molecular level using automated flexible docking combined with multidimensional QSAR (mQSAR). Currently, those targets comprise 12 proteins: the androgen, aryl hydrocarbon, estrogen alpha/beta, glucocorticoid, mineralocorticoid, thyroid alpha/beta liver X and the peroxisome proliferator-activated receptor gamma as well as the enzymes cytochrome P450 3A4 (CYP 3A4) and 2A13 (CYP 2A13). Up to date, the technology has been used to predict the toxic potential for more than 2,000 drugs, chemicals and natural compounds. All results are posted in the Internet - in this account, a few will be discussed in detail with reference to the molecular mechanisms triggering the adverse effect.
Vedani
Angelo
A
Biographics Laboratory 3R, CH-Basel and Department of Pharmaceutical Sciences, University of Basel, Switzerland. admin@biograf.ch
Smiesko
Martin
M
Spreafico
Morena
M
Peristera
Ourania
O
Dobler
Max
M
D001688:Biological Products / Q000009:adverse effects* / Q000737:chemistry; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions; D052244:Endocrine Disruptors / Q000009:adverse effects* / Q000737:chemistry; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D012984:Software
D001688:Biological Products; D052244:Endocrine Disruptors; D004364:Pharmaceutical Preparations