Quantitative Structure–Activity Relationship (QSAR) Modeling of EC₅₀of Aquatic Toxicities forDaphnia magna

Abstract

The experimental EC(50) toxicities toward Daphnia magna for a series of 130 benzoic acids, benzaldehydes, phenylsulfonyl acetates, cycloalkane-carboxylates, benzanilides, and other esters were studied using the Best multilinear regression algorithm (BMLR) implemented in CODESSA. A modified quantitative structure-activity relationships (QSAR) procedure was applied guaranteeing the stability and reproducibility of the results. Separating the initial data set into training and test subsets generated three independent models with an average R(2) of .735. A five-descriptor general model including all 130 compounds, constructed using the descriptors found effective for the independent subsets, was characterized by the following statistical parameters: R(2) = .712; R(2)(cv) = .676; F = 61.331; s(2) = 0.6. The removal of two extreme outliers improved significantly the statistical parameters: R(2) = .759; R(2)(cv) = .728; F = 77.032; s(2) = 0.499. The sensitivity of the general model to chance correlations was estimated by applying a scrambling procedure involving 20 randomizations of the original property values. The resulting R(2) = .192 demonstrated the high robustness of the model proposed. The descriptors appearing in the obtained models are related to the biochemical nature of the adverse effects. An additional study of the EC(50)/LC(50) relationship for a series of 28 compounds (part of our general data set) revealed that these endpoints correlated with R(2) = .98.

QSTR modeling for predicting aquatic toxicity of pharmacological active compounds in multiple test species for regulatory purpose

“…Selected descriptors for classification and regression QSTRs constructed here belong to topological (SP-4, VP-0, VP-5, VPC-4, MDEC-23, MDEO-11, Chi0C, ATSm2), electronic (RPCS), geometrical (MOMI-X), constitutional (XlogP, nRotB, nAP, nAA), and physico-chemical (LogS) categories. Since the most toxic compounds are characterized by low LC 50 (and respectively high pLC 50 ) values, all descriptors having positive correlation coefficients (except LogS, MDEO-11, RPCS) increase the adverse effect, whereas negative correlation coefficients led to a decreased toxicity effect (Katritzky et al 2009). From Fig.…”

“…Partitioning of the molecule into the hydrophobic phase (membrane) permits it to interfere with the organism. Hence, the LogP descriptor might be related to their ability to penetrate through the cell membrane and reach the target site (Katritzky et al, 2009). The topological descriptors help to differentiate the molecules according mostly to their size, degree of branching, flexibility, and overall shape.…”

“…It is an important primary consumer of primitive plant life and itself a major food source for vertebrate and invertebrate predators and has been used as a representative for other freshwater animals in standard tests of toxicity (OECD, 1984) because of its high sensitivity, easy handling and high reproductive rate (Katritzky et al, 2009). Daphnia acute toxicity (48 h) test is used for short term toxicity (LC 50 ) assessment of chemicals.…”

Occurrence and ecological hazard assessment of selected veterinary medicines in livestock wastewater treatment plants

“…This is because the toxicity of each compound was highly dependent upon rather narcosis than log Kow. [36,37] Organic chemicals can be divided into non-polar narcosis (Narcosis I) and polar narcosis (Narcosis II). Narcosis I compounds such as n-octanol, 1,2-dichlorobenzene, and 2-butanone are considered to have the least toxic mode of action and are often called "baseline toxicity".…”

“…As shown in Figure 4, the numbers of hydrogen bonding acceptors were proportional to log Dow. Katritzky et al [36] stated that the most toxic compounds act mainly as hydrogen bonding acceptors. In other words, this shows that the toxicity of a compound is a mainly function of the steric characteristics.…”