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    Acute toxicities of 25 substituted biphenyls to Daphnia magna were determined. 18 tested chemicals exhibit toxicity. A Quantitative Structure‐Activity Relationship (QSAR) was developed as the following: It can be used to predict the toxicity of substituted biphenyls under this experimental condition. At the same time, it also showed that lipophilicity and polarizability may be of major importance in influencing the toxicity of these studied chemicals. Chemicals with higher log Kow and α have greater toxicity.
    Daphnia magna
    Lipophilicity
    Citations (0)
    Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance's database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (LD₅₀) for determining relative toxicity of a number of substances. In general, the smaller the LD₅₀ value, the more toxic the chemical, and the larger the LD₅₀ value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s) of interest, during emergency responses, LD₅₀ values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD₅₀ models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD) are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD₅₀ values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field.
    Sulfur mustard
    Citations (49)
    There are more than 70000 chemicals in use today and many more being synthesized. It is vital to assess the influence of these compounds on the environment and on human health. Experimental testing is both time-consuming and expensive, and accordingly, there is a pressing requirement for accurate in silico methods to assess the toxicity. QSAR studies of the environmental fate of chemicals are widely used for this purpose. One of the broadly used toxicity database is the Distributed Structure-Searchable Toxicity (DSSTox) database from the U.S. Environmental Protection Agency (http://www.epa.gov). It provides various data including EPA Fathead Minnow Aquatic Toxicity Database (EPAFHM), which currently contains structures of 617 chemicals of which 580 structures have toxicity data (EPAFHM_v3b_617_10Apr2006). The toxicity end-points are based on the 96 h LC50 (mmol/L) values for the fathead minnow, which used for standard toxicity test described by the U.S. Environmental Protection Agency. We used QNA (Quantitative Neighbourhoods of Atoms) descriptors and Self-Consistent Regression for QSAR modeling of acute toxicity in the fathead minnow. The statistical parameters of the correlation are the follows: N = 580, R2 = 0.804, F = 32.508, SD = 0.670, Q2 = 0.759. For 522 compounds (90%), the deviation of the predicted values from the observed ones is less than 1 logLC50 (mmol/L). Leave-10%-out cross-validation procedure was used for assessment of prediction ability of the method. It was performed 20 times and average R2 of prediction was 0.606, the highest value of R2 = 0.815, the lowest value of R2 = 0.501. Applicability domain was estimated for test set by leave-10%-out cross-validation procedure. These results confirmed robustness and satisfactory predictive ability of the method, hence, it can be used for computational assessment of acute toxicity in new compounds.
    Aquatic toxicology
    Abstract A critical review is given of quantitative structure‐activity relationships (QSAR) for the prediction of mammalian toxicological endpoints. QSAR predictions for mammalian toxicity are generally poorly developed although hydrophobicity correlates well with the toxicity of unreactive chemicals. Interspecies correlations of acute toxicity are discussed and when the mode of toxic action is taken into account these may provide a valuable source of information for comparative toxicity and the potential use of surrogate species for testing.
    Citations (55)