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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. [ABSTRACT FROM AUTHOR]

Nuclear retinoic acid receptor a (RARα) activates gene expression through dynamic interactions with coregulatory protein complexes, the assembly of which is directed by the ligand and the AF-2 domain of RARα. Then RARa and its coactivator SRC-3 are degraded by the proteasome. Recently it has emerged that the proteasome also plays a key role in RARamediated transcription. Here we show that SUG-1, one of the six ATPases of the 19 S regulatory complex of the 26 S proteasome, interacts with SRC-3, is recruited at the promoters of retinoic acid (RA) target genes, and thereby participates to their transcription. In addition, SUG-1 also mediates the proteasomal degradation of SRC-3. However, when present in excess amounts, SUG-1 blocks the activation of RARa target genes and the degradation of RARa that occurs in response to RA, via its ability to interfere with the recruitment of SRC-3 and other coregulators at the AF-2 domain of RARα. We propose a model in which the ratio between SUG-1 and SRC-3 is crucial for the control of RARa functioning. This study provides new insights into how SUG-1 has a unique role in linking the transcription and degradation processes via its ability to interact with SRC-3. [ABSTRACT FROM AUTHOR]