Investigation On The Rat Acute Toxicity Of Organic Pollutants And Biodegradation Based On Fragmentation Scheme

Organic pollutants, as chemical raw materials, are the main pollutants in the environment. Due to their widespread distribution and high toxicity, organic pollutants severely polluted rivers, lakes, oceans, and groundwater ecosystem. The pollutants, which transfer to soils and water environment, will move up the food chain and accumulate in certain tissues of organisms. Others which enter thebiological germ cells, will change the organism’s genetic material, or even destroy the biological genetic function. Investigation on the toxic effects and the fate of organic pollutants will contribute to assess the ecological risk. Therefore, research on the acute toxicity of organic pollutants to rats and microbial biodegradation of organic pollutants, is one of the problem concerned by all countries around the world. Recently, although MOAs of industrial chemicals for aquatic toxic effects are well developed and investigated, there are few literatures reported for mammal toxic effects. Most of these researches for rat toxicity were derived from limited data sets of structurally similar chemicals. As a consequence, no systematic efforts have been made to rat toxicity for industrial chemicals and their MOAs are not clear, also no systematic study on comparing the MOAs between the organic pollutant toxicity to aquatic organisms and mammalian. On the other hand, the process of developing the model of the quantitative structure-biodegradability relationship(QSBR) has made some achievements, but most models have been developed for selected groups of structurally similar compounds. The dominant factor is that this method(structural fragment scheme) needs to be based on a large number of high quality experimental data.This paper uses a large number of industrial organic pollutants as the research object, carries out the investigation on organic pollutants to rats and fish toxicity mechanism, as well as the prediction of organic pollutant biodegradation and metabolic pathway and mechanism. The investigation results were summarized as follows:(1) The aim of this paper was to investigate the baseline toxicity to rats and the effect of exposure routes on toxicity. The results showed that rat toxicity(log 1/LD50) varies around a constant for each specific class. The toxicity ratio(TR) indicated that toxicity of compounds to rats was much more sensitive than toxicity to fish. Small changes in chemical structure can result in different toxic effect. The threshold used in fish toxicity was too high to distinguish toxic differences between chemical classes. Critical body residues(CBR) calculated from percentage of absorption and bioconcentration factors indicated that simple aliphatic chemicals may share the same modes of toxic action between rat and fish species. The classification of excess toxicity should be based on the CBR, rather than the TR because the TR is closely related to the exposure routes. The high estimation error of bioconcentration factor calculated from octanol/water partition coefficient can result in significantly incorrect classifications in modes of toxic action for fish toxicity.(2) In this paper, multi-linear regression analysis was performed between rat toxicities(log1/LD50) and substructures for 1255 aromatic compounds. The toxic contributions of functional groups in aromatic compounds were calculated from the regression and were then compared with the toxic contributions in aliphatic compounds. The results show that some functional groups have same toxic contributions both in aromatic and aliphatic compounds, but some did not. Additive effects were not found in aliphatic compounds for multi-substituted functional groups, but were observed in aromatic compounds. To investigate the MOAs in rat toxicity, the distribution of toxic ratio(TR) was examined for well-known baseline and less inert compounds and thresholds of log TR = 3 and 5 were used to classify baseline, less inert and reactive compounds. The results showed that some compounds, such as alkanes, alkenes, alcohols, ketones and alkyl benzenes were identified as baseline compounds in fish toxicity, were also classified as baseline compounds in rat toxicity. On the other hand, except for phenols and anilines which were identified as less inert compounds in fish toxicity, aromatic compounds with functional groups such as ether, nitrile, mono-nitrophenol, isocyanatoe and chloro were identified as less inert chemicals in rat toxicity. Investigation on the reactive compounds showed that reactive compounds identified in fish toxicity exhibit greater toxicity to rats. These compounds can undergo nucleophilic substitution, acylation and Schiff base formation with biological macromolecules. The critical body residues(CBR) calculated from percentage of absorption and bioconcentration show that log CBR in rat toxicity are close to CBR in fish for some compounds. It suggests that they share the same MOAs between these two species for these compounds.(3) In this paper, linear and nonlinear relationships between biological oxygen demand(BOD) and molecular descriptors/fragments have been investigated for 1130 organic chemicals. Significant relationships have been observed between the simple molecular descriptors and %BOD for some homologous compounds, but not for the whole set of compounds. Electronic parameters, such as EHOMO and ELUMO, are the dominant factors affecting the biodegradability for some homologous chemicals. However, other descriptors, such as molecular weight, acid dissociation constant and polarity still have a significant impact on the biodegradation. The best global model for %BOD prediction is developed from a chain-based fragmentation scheme. At the same time, the theoretical relationship between %BOD and molecular descriptors/fragments has been investigated, based on a first-order kinetic process. The %BOD is nonlinearly, rather than linearly, related to the descriptors. The coefficients of determination can be significantly improved by using nonlinear models for the homologous compounds and the whole data set. After analysing 1130 ready and not ready biodegradable compounds using 23 simple descriptors and various fragmentation schemes, it was revealed that biodegradation could be well predicted from a chain-based fragmentation scheme, a decision tree and a %BOD model. The models were capable of separating NRB and RB with an overall accuracy of 87.2%, 83.0% and 82.5%, respectively. The best classification model developed was a chain-based model but it used 155 fragments. The simplest model was a decision tree which only used 10 structural fragments. The effect of structures on the biodegradation has been analysed and the biodegradation pathway and mechanisms have been discussed based on activating and inactivating fragments.