VirtualToxLab – in silico Prediction of the Endocrine-Disrupting Potential of Drugs and Chemicals
Author(s) -
Angelo Vedani,
Morena Spreafico,
Ourania Peristera,
Max Dobler,
Martin Smieško
Publication year - 2008
Publication title -
chimia international journal for chemistry
Language(s) - English
Resource type - Journals
eISSN - 2673-2424
pISSN - 0009-4293
DOI - 10.2533/chimia.2008.322
Subject(s) - in silico , quantitative structure–activity relationship , aryl hydrocarbon receptor , endocrine system , computational biology , chemistry , virtual screening , cytochrome p450 , pharmacology , biology , transcription factor , biochemistry , hormone , drug discovery , enzyme , stereochemistry , gene
In the last decade, we have developed and validated an in silico concept based on multidimensional QSAR (mQSAR) for the prediction of the toxic potential of drugs and environmental chemicals. Presently, the VirtualToxLab includes eleven so-called virtual test kits for estrogen (α/β), androgen, thyroid (α/β), glucocorticoid, aryl hydrocarbon, mineralocorticoid and peroxisome proliferator-activated receptor y as well as for the enzymes cytochrome P450 3A4 and 2A13. The surrogates have been tested against a total of 824 compounds and are able to predict the binding affinity close to the experimental uncertainty with only six of the 194 test compounds giving calculated results more than a factor of 10 off the experimental binding affinity and the maximal individual deviation not exceeding a factor of 15. These results suggest that our approach is suited for the in silico identification of endocrine-disrupting effects triggered by drugs and environmental chemicals. Most recently, the technology has been made available through the Internet for academic laboratories, hospitals and environmental organizations.
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