Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool (in silico) to rapidly predict various endpoints in general, and drug toxicity in particular. However, this dynamic evolution of experimental data (expansion of existing experimental data on drugs toxicity) leads to the problem of critical estimation of the data. The carcinogenicity, mutagenicity, liver effects and cardiac toxicity should be evaluated as the most important aspects of the drug toxicity. The toxicity is a multidimensional phenomenon. It is apparent that the main reasons for the increase in applications of in silico prediction of toxicity include the following: (i) the need to reduce animal testing; (ii) computational models provide reliable toxicity prediction; (iii) development of legislation that is related to use of new substances; (iv) filling data gaps; (v) reduction of cost and time; (vi) designing of new compounds; (vii) advancement of understanding of biology and chemistry. This mini-review provides analysis of existing databases and software which are necessary for use of robust computational assessments and robust prediction of potential drug toxicities by means of in silico methods.

3rd Department of Medicine Department of Endocrinology and Metabolism 1st Faculty of Medicine Charles University Prague and General University Hospital Prague U Nemocnice 1 12808 Prague 2 Czech Republic

Interdisciplinary Nanotoxicity Center Department of Chemistry and Biochemistry Jackson State University 1400 J R Lynch Street PO Box 17910 Jackson MS 39217 USA

Interdisciplinary Nanotoxicity Center Department of Civil and Environmental Engineering Jackson State University 1325 Lynch St Jackson MS 39217 0510 USA

IRCCS Istituto di Ricerche Farmacologiche Mario Negri IRCCS Via La Masa 19 Milano 20156 Italy

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