Non-specific toxicants

On the other hand, compounds corresponding to rather general, unspecific inodes of toxic action are distributed over a broad area in the respective layer, as shown for polar non-specific toxicants in Figure 10.1-14. 

Figure 10.1-14. Distributfon of compounds in the layer of polar non-specife toxicants.

Liposomal preparations can be therapeutically beneficial based on their ability to decrease non-specific toxicities associated with the drug, or by being more efficacious against a specific type of cancer, increasing the response frequency, and/or the average time to relapse or response duration. 

Several vitro assays for detecting fermentation products with anthelmintic activity had been run without success, primarily because of the large number of toxic compounds which had to be eliminated. Finally, the decision was made to use an vivo assay in mice with the hope that the mice would screen out the non-specific toxic compounds. 

Figure 13 outlines our retrosynthetic analysis of epothilone D (49). Since epoxidation of epothilone D to give epothilone B (3) is the last step in all total syntheses of the latter, this is considered to be trivial. Furthermore, epothilone D shows a lower non-specific toxicity relative to its antimitotic properties. 

Non-specific toxic liver damage may be evident in this connection, possible tuberculostatic toxic effects must also be considered. With severe courses of tuberculosis, peliosis hepatis is often observed. Frequently, retothelial nodules are detectable, as demonstrated for the first time in tuberculosis patients by H. Hamperl in 1953. (50) In the course of chronic pulmonary tuberculosis,infiltration of liver cells was noted, as reported in several publications. (50) It was attributed to toxic effects and/or undernourishment or malnutrition. Secondary hepatic amyloidosis, developing in the course of chronic lung tuberculosis, has also been postulated. (50) A restriction of hepatic function in chronic tuberculosis, which was first observed by E. Leuret et al. in 1922, has been described in a number of publications. (51, 60, 63) Depending on the severity and duration of the disease as well as the tuberculostatic pretreatment, we found pathological laboratory parameters in 15-20% and 25-40% of cases respectively. (50)... 

Pyrithione zinc s action is thought to be due to a non-specific toxicity for epidermal cells selenium sulphide is believed to have a direct antimitotic effect. 

With respect to toxicity and side effects, only limited in vivo data are available. As most of the compounds in clinical testing are SODNs, it is clear that some of the non-specific toxicity data presented in Table 16 are closely related to this class of backbone-modified compounds. 

When any species is exposed to xenobiotics, the minimum effects observed are evoked by partitioning into lipid phases. This so-called non-specific toxicity (baseline toxicity) is caused by membrane perturbation, predominant with many environmentally relevant chemicals. The membrane lipid and pro-... 

Figure 5.3 Example of the discrimination of different modes of action based on testing with a battery of specific in vitro assays. The overlap of class domains indicates the ambiguity of assignments for chemicals with multiple modes of action. NST = non-specific toxicants DC = uncouplers PS = inhibitors of photosynthesis AChE = AChE inhibitors RA = reactive compounds SH = SH blocker RB = respiratory blocker. Reproduced from Nendza, Wenzel and Wienen (1995) with permission from Gordon and Breach Publishers, Lausanne.

For hazard-evaluation purposes, fish toxicants are roughly divided into two categories the non-specific toxicants (Table 5.2) and a heterogeneous group of specifically acting toxicants. 

Table 5.2 Structural characteristics of nonpolar non-specific toxicants towards fish.

These structural requirements are not exhaustive other compounds may also fall into the group of the non-polar non-specific toxicants. However, compounds complying with these rules may be much more toxic than baseline (Verhaar, Leeuen and Hermens, 1992). 

Figure 5.4 Comparison of selected QSAR models for non-polar non-specific toxicants relating log I/LC50 to log Pqw experimental data on fish lethality (Brooke et al., 1984 Geiger et a/., 1985, 1986, 1988,1990) for identification of the QSAR functions see Table 5.3.

Similar relationships have also been derived with other descriptors that are generally collinear with log for non-polar non-specific toxicants for example, water solubility (Konemann, 1981b Zaroogian et al., 1985), topological indices (Basak and Magnuson, 1983 Koch, 1983 Sabljic, 1983), or with substructure indicators (Hall, Maynard and Kier, 1989), which may be applied if the log P of the test compounds cannot be estimated, and also to cross-check the predictions obtained, especially when there is reasonable doubt about the correctness of the respective log P values. 

Table 5,3 Examples of QSAR models for estimating toxicity to fish of non-polar non-specific toxicants (e.g. alkanes, alkenes, saturated and unsaturated halogenated aliphatic hydrocarbons, basic ethers, cyclic ethers, ketones, amides, secondary and tertiary aliphatic and aromatic amines, alkylbenzenes, halogenated benzenes, piperazines, pyrimidines, polychlorinated hydrocarbon pesticides) log LC50 correlations with various parameters. 

The elevated specific toxicity results in increased intercepts (approximately 0) again, whereas the slopes are congruent with QSAR models for polar non-specific toxicants, indicating that the amount of the uncouplers excess toxicity is essentially independent of their log (Figure 5.6). 

The slopes and the intercepts are similar to those of the fish baseline models (about 0.8-1 and -2 on the mmol/1 scale respectively), indicating a similar sensitivity of fish and daphnids towards non-specific toxicants. The derivation of almost identical models by different investigators with different sets of chemicals supports the reliability of these baseline QSARs for estimating the toxicity of non-polar non-reactive chemicals to Daphnia. Any compound is expected to be at least as toxic as predicted from these models. 

Table 5.6 Examples of QSAR models for estimating toxicity to Daphnia of non-polar, non-specific toxicants log EC50 correlations with various parameters. 

Comparison of measured data on acute toxicity with calculated baseline predictions revealed that 21.5% of the compounds (53 out of 246) were at least five times more toxic towards Daphnia than estimated, whereas almost 80% had non-specific toxicity. The identification of potential outliers from the baseline QSAR models based on the set of reactive substructures derived from fish tests (section 5.1) is only partly satisfactory 19 outliers (35.8%) were recognized from their substructures and seven baseline toxicants (3.6%) were incorrectly assumed to exert excess toxicity (Jackel and Nendza, 1994). Those compounds with reactive substructures actually show excess toxicity towards Daphnia, but not all outliers are recognized. Accordingly, the set of indicators devised for fish has to be adjusted to cover different modes of action on specific targets in different organisms. 

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