Non-linear modeling of bioconcentration using partition coefficients for narcotic chemicals

Bioconcentration factors (BCFs) have traditionally been used to describe the tendency of chemicals to concentrate in aquatic organisms. A reexamination of the log-log QSAR between the BCF and K OW for non-congener narcotic chemicals is presented on the basis of recommended data for fish. The model is extended to give a simple correlation between BCF and the toxicity of highly, moderately and weakly hydrophilic chemicals. For the first time, in this study an equation for calculating BCF was applied in a QSAR model for predicting the acute toxicity of chemicals to aquatic organisms.     

Assessment and validation of the CAESAR predictive model for bioconcentration factor (BCF) in fish

Background

Bioconcentration factor (BCF) describes the behaviour of a chemical in terms of its likelihood of concentrating in organisms in the environment. It is a fundamental property in recent regulations, such as the European Community Regulation on chemicals and their safe use or the Globally Harmonized System for classification, labelling and packaging. These new regulations consider the possibility of reducing or waiving animal tests using alternative methods, such as in silico methods. This study assessed and validated the CAESAR predictive model for BCF in fish.

Results

To validate the model, new experimental data were collected and used to create an external set, as a second validation set (a first validation exercise had been done just after model development). The performance of the model was compared with BCFBAF v3.00. For continuous values and for classification purposes the CAESAR BCF model gave better results than BCFBAF v3.00 for the chemicals in the applicability domain of the model. R² and Q² were good and accuracy in classification higher than 90%. Applying an offset of 0.5 to the compounds predicted with BCF close to the thresholds, the number of false negatives (the most dangerous errors) dropped considerably (less than 0.6% of chemicals).

Conclusions

The CAESAR model for BCF is useful for regulatory purposes because it is robust, reliable and predictive. It is also fully transparent and documented and has a well-defined applicability domain, as required by REACH. The model is freely available on the CAESAR web site and easy to use. The reliability of the model reporting the six most similar compounds found in the CAESAR dataset, and their experimental and predicted values, can be evaluated.

     

Tests of a “free-volume” model of gas permeation through polymer membranes. I. Pure CO2, CH4, C2H4, and C3H8 in polyethylene

Permeability coefficients have been measured for CO₂, CH₄, C₂H₄, and C₃H₈ in polyethylene membranes at temperatures of 5, 20, and 35°C and at applied gas pressures of up to 30 atm. The temperature and pressure dependence of the permeability coefficients was represented satisfactorily by an extension of Fujita's free-volume model of diffusion of small molecules in polymers. The results of the present steady-state permeability measurements provide further support for the conclusion reached from previous unsteady-state diffusivity measurements that Fujita's model is applicable to the transport of small molecules, such as CO₂, CH₄, C₂H₄, and C₃H₈, in polyethylene. It was previously thought that this model is applicable only to the transport of larger molecules, such as of organic vapors, in polymers.     

Base-line model for identifying the bioaccumulation potential of chemicals

The base-line modeling concept presented in this work is based on the assumption of a maximum bioconcentration factor (BCF?) with mitigating factors that reduce the BCF. The maximum bioconcentration potential was described by the multi-compartment partitioning model for passive diffusion. The significance of different mitigating factors associated either with interactions with an organism or bioavailability were investigated. The most important mitigating factor was found to be metabolism. Accordingly, a simulator for fish liver was used in the model, which has been trained to reproduce fish metabolism based on related mammalian metabolic pathways. Other significant mitigating factors, depending on the chemical structure, e.g. molecular size and ionization were also taken into account in the model. The results (r ²?=?0.84) obtained for a training set of 511 chemicals demonstrate the usefulness of the BCF base line concept. The predictability of the model was evaluated on the basis of 176 chemicals not used in the model building. The correctness of predictions (abs(log?BSF? ^Obs???log?BCF? ^Calc)?≤?0.75)) for 59 chemicals included within the model applicability domain was 80%.     

The kinetics of solid-phase microextraction measured for freshly added and aged hydrophobic compounds in two different soils

The proper choice of exposure times is critical if the freely dissolved concentration of chemicals in soil porewater is to be measured via the equilibrium solid-phase microextraction (SPME) as the times to equilibrium may vary depending on compound and soil properties. To reveal the effects of compound hydrophobicity, ageing and soil organic matter content on times to equilibrium, the SPME uptake was measured for five freshly added and aged hydrophobic organic compounds (phenanthrene, pyrene, lindane, p,p′-DDT and polychlorinated biphenyl (PCB) 153) in two contrasted soils (arable and forest soil). The tested compound-soil systems behaved kinetically different. Longer equilibrium times were observed with increasing hydrophobicity of compounds for aged compared to freshly added chemicals and for the forest soil in comparison to the arable soil. The calculated soil–porewater partition coefficients (i.e. sorption coefficients, K_d) of chemicals differed between soil types mainly due to various organic carbon (OC) contents as evidenced by the comparable K_oc values (i.e. K_d values normalised to soil OC content). Similar K_oc values were also found with the various extent of ageing, indicating that both the freshly added and aged compounds linearly partitioned between the soil organic matter and porewater. Our results suggest that, for a respective compound, variations in equilibrium times may be expected depending upon the residence time and the organic matter content in soil where the longest equilibrium times seems to appear for a combination of aged compounds and high organic soils. With regard to this outcome, the effect of the level of sample depletion due to the SPME extraction (LD_SPME) on equilibrium times was assessed. At LDs_SPME of up to 10%, equilibrium times increases linearly with LDs_SPME for p,p′-DDT and PCB 153. For phenanthrene (LD_SPME<10%), and for lindane and pyrene (1.2% < LD_SPME > 40%), no clear relationships were observed.     

Nonlinear Dependence of Fish Bioconcentration on n-Octanol/Water Partition Coefficient

Abstract

The log-log relationship between the bioconcentration tendency of organic chemicals in fish and the n?octanol/water partition coefficients breaks down for very hydrophobic compounds. The use of parabolic and bilinear models allows this problem to be overcome. The QSAR equation log BCF = 0.910 log P - 1.975 log (6.8 10^?7 P + 1) - 0.786 (n = 154; r = 0.950; s = 0.347; F = 463.51) was found to be a good predictor of bioconcentration in fish.     

Quantitative prediction of biodegradability,metabolite distribution and toxicity of stable metabolites

An evaluation of the capability of organic chemicals to mineralize is an important factor to consider when assessing their fate in the environment. Microbial degradation can convert a toxic chemical into an innocuous one, and vice versa , or alter the toxicity of a chemical. Moreover, primary biodegradation can convert chemicals into stable products that can be difficult to mineralize. In this paper, we present some new results obtained on the basis of a recently developed probabilistic approach to modeling biodegradation based on microbial transformation pathways. The metabolic transformations and their hierarchy were calibrated by making use of the ready biodegradability data from the MITI-I test and expert knowledge for the most probable transformation pathways. A model was developed and integrated into an expert software system named CATABOL that is able to predict the probability of biodegradation of organic chemicals directly from their structure. CATABOL simulates the effects of microbial enzyme systems, generates the most plausible transformation pathways, and quantitatively predicts the persistence and toxicity of the biodegradation products. A subset of 300 organic chemicals were selected from Canada's Domestic Substances List and subjected to CATABOL to compare predicted properties of the parent chemicals with their respective first stable metabolite. The results show that most of the stable metabolites have a lower acute toxicity to fish and a lower bioaccumulation potential compared to the parent chemicals. In contrast, the metabolites appear to be generally more estrogenic than the parent chemicals.     

U.S. EPA Regulatory Perspectives on the Use of QSAR for New and Existing Chemical Evaluations

Abstract

As testing is not required, ecotoxicity or fate data are available for ≈ 5% of the approximately 2,300 new chemicals/year (26,000 + total) submitted to the US-EPA. The EPA's Office of Pollution Prevention and Toxics (OPPT) regulatory program was forced to develop and rely upon QSARs to estimate the ecotoxicity and fate of most of the new chemicals evaluated for hazard and risk assessment. QSAR methods routinely result in ecotoxicity estimations of acute and chronic toxicity to fish, aquatic invertebrates, and algae, and in fate estimations of physical/chemical properties, degradation, and bioconcentration. The EPA's Toxic Substances Control Act (TSCA) Inventory of existing chemicals currently lists over 72,000 chemicals. Most existing chemicals also appear to have little or no ecotoxicity or fate data available and the OPPT new chemical QSAR methods now provide predictions and cross-checks of test data for the regulation of existing chemicals. Examples include the Toxics Release Inventory (TRI), the Design for the Environment (DfE), and the OECD/SIDS/HPV Programs. QSAR screening of the TSCA Inventory has prioritized thousands of existing chemicals for possible regulatory testing of: 1) persistent bioaccumulative chemicals, and 2) the high ecotoxicity of specific discrete organic chemicals.     

QSARs for identifying and prioritizing substances with persistence and bioconcentration potential

From the 8511 chemicals with 1998 production volumes reported to the U.S. Environmental Protection Agency (U.S. EPA), the TSCA Interagency Testing Committee's (ITC's) Degradation Effects Bioconcentration Information Testing Strategies (DEBITS) was used to identify 56 chemicals. The DEBITS Quantitative Structure-Activity Relationships (QSARs) and the U.S. EPA's PBT profiler QSARs were used to predict the persistence and bioconcentration factors of these 56 chemicals. Partial order ranking was used to prioritise the chemicals based on persistence and bioconcentration potential.     

Modeling the Environmental Fate of Atrazine

Abstract

Mathematical simulation models of fate and transport of chemicals have been identified by researchers and regulators as potentially valuable tools for improving the understanding of the environmental behavior of chemicals which may be released to the environment as a consequence of routine (i.e., normal manufacturing, use, disposal) and non-routine (e.g., accidental spillage) events. In this context, CHEMFRANCE, a regional fugacity model level III, which calculates the environmental distribution of organic chemicals in 12 defined regions of France, or France as a whole, has been designed. The aim of this study is to show that CHEMFRANCE provides valuable simulation results for understanding the environmental fate behavior of atrazine.     

Predicting the Standard Enthalpy (ΔHo f) and Entropy (So) of Alkanes by Artificial Neural Networks

Abstract

Artificial Neural Networks (ANNs) with Extended Delta-Bar-Delta (EDBD) back propagation learning algorithm have been developed to predict the standard enthalpy and entropy of 87 acyclic alkanes. Molecular weight, boiling point and density of the compounds were used as input parameters. The network's architecture and parameters were optimized to give maximum performances. The best network was a 3-6-2 ANN, and the optimum learning epoch was about 1320. The results show that the maximum relative errors of enthalpy and entropy are less than 3%. They reveal that the performances of ANNs for predicting the enthalpy and entropy of alkanes are satisfying.     

The numerical solution of fujita's integral equation to provide estimates of molecular weight distributions

A standard model of the behavior of polymers under ultracentrifugation results in Fujita's equation for their molecular weight distribution. Fujita's and related equations are examples of Fredholm integral equations of the first kind and are thus ill posed. Two methods are described for solving the equations numerically and hence providing estimates of the molecular weight distribution. The first method involves expanding the distribution in terms of orthogonal polynomials whose coefficients are calculated from estimates of the moments of the distribution. In the second method the distribution is reconstructed by using matrix singular-value decomposition techniques combined with an approximant expressed as a sum of B-splines. The potential and practical limitations associated with the methods are illustrated by numerical results from a series of tests on four problems designed to represent distributions with different modal properties.     

Systematic Enumeration and Symmetries of Cubane Derivatives

The feasibilities of Fujita's unit‐subduced‐cycle‐index (USCI) approach, Fujita's proligand method, and Fujita's stereoisogram approach have been demonstrated by applying them to cubane derivatives as probes. They provide us with a new set of theoretical foundations for comprehensive investigation of geometric and stereoisomeric features of stereochemistry. The new set of theoretical foundations is based on mathematical formulations so as to explore mathematical stereochemistry as a new interdisciplinary field of stereochemistry.