Comprehension of drug toxicity: software and databases.
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.
IRCCS, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via La Masa 19, Milano 20156, Italy. Electronic address: andrey.toropov@marionegri.it.
Andrey A
AA
Toropov
IRCCS, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via La Masa 19, Milano 20156, Italy.
Alla P
AP
Toropova
3rd Department of Medicine, Department of Endocrinology and Metabolism, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, U Nemocnice 1, 12808 Prague 2, Czech Republic.
Ivan
I
Raska
Interdisciplinary Nanotoxicity Center, Department of Civil and Environmental Engineering, Jackson State University, 1325 Lynch St, Jackson, MS 39217-0510, USA.
Danuta
D
Leszczynska
Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 J. R. Lynch Street, PO Box 17910, Jackson, MS 39217, USA.
Jerzy
J
Leszczynski
D000818:Animals; D019295:Computational Biology; D003198:Computer Simulation; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D021281:Quantitative Structure-Activity Relationship; D012984:Software; D018675:Toxicity Tests
Computational toxicology; Drug toxicity; In silico methods; In silico toxicology; QSAR