A kinetic model for predicting biodegradation

Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a ‘10?day window’ criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the ‘10-day window’ criterion.     

Probabilistic assessment of biodegradability based on metabolic pathways: catabol system

A novel mechanistic modeling approach has been developed that assesses chemical biodegradability in a quantitative manner. It is an expert system predicting biotransformation pathway working together with a probabilistic model that calculates probabilities of the individual transformations. The expert system contains a library of hierarchically ordered individual transformations and matching substructure engine. The hierarchy in the expert system was set according to the descending order of the individual transformation probabilities. The integrated principal catabolic steps are derived from set of metabolic pathways predicted for each chemical from the training set and encompass more than one real biodegradation step to improve the speed of predictions. In the current work, we modeled O2 yield during OECD 302 C (MITI I) test. MITI-I database of 532 chemicals was used as a training set. To make biodegradability predictions, the model only needs structure of a chemical. The output is given as percentage of theoretical biological oxygen demand (BOD). The model allows for identifying potentially persistent catabolic intermediates and their molar amounts. The data in the training set agreed well with the calculated BODs (r2 = 0.90) in the entire range i.e. a good fit was observed for readily, intermediate and difficult to degrade chemicals. After introducing 60% ThOD as a cut off value the model predicted correctly 98% ready biodegradable structures and 96% not ready biodegradable structures. Crossvalidation by four times leaving 25% of data resulted in Q2 = 0.88 between observed and predicted values. Presented approach and obtained results were used to develop computer software for biodegradability prediction CATABOL.     

Probabilistic assessment of biodegradability based on metabolic pathways: CATABOL System

A novel mechanistic modeling approach has been developed that assesses chemical biodegradability in a quantitative manner. It is an expert system predicting biotransformation pathway working together with a probabilistic model that calculates probabilities of the individual transformations. The expert system contains a library of hierarchically ordered individual transformations and matching substructure engine. The hierarchy in the expert system was set according to the descending order of the individual transformation probabilities. The integrated principal catabolic steps are derived from set of metabolic pathways predicted for each chemical from the training set and encompass more than one real biodegradation step to improve the speed of predictions. In the current work, we modeled O 2 yield during OECD 302 C (MITI I) test. MITI-I database of 532 chemicals was used as a training set. To make biodegradability predictions, the model only needs structure of a chemical. The output is given as percentage of theoretical biological oxygen demand (BOD). The model allows for identifying potentially persistent catabolic intermediates and their molar amounts. The data in the training set agreed well with the calculated BODs ( r 2 =0.90) in the entire range i.e. a good fit was observed for readily, intermediate and difficult to degrade chemicals. After introducing 60% ThOD as a cut off value the model predicted correctly 98% ready biodegradable structures and 96% not ready biodegradable structures. Crossvalidation by four times leaving 25% of data resulted in Q 2 =0.88 between observed and predicted values. Presented approach and obtained results were used to develop computer software for biodegradability prediction CATABOL.     

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.     

External validation of EPIWIN biodegradation models

The BIOWIN biodegradation models were evaluated for their suitability for regulatory purposes. BIOWIN includes the linear and non-linear BIODEG and MITI models for estimating the probability of rapid aerobic biodegradation and an expert survey model for primary and ultimate biodegradation estimation. Experimental biodegradation data for 110 newly notified substances were compared with the estimations of the different models. The models were applied separately and in combinations to determine which model(s) showed the best performance. The results of this study were compared with the results of other validation studies and other biodegradation models. The BIOWIN models predict not-readily biodegradable substances with high accuracy in contrast to ready biodegradability. In view of the high environmental concern of persistent chemicals and in view of the large number of not-readily biodegradable chemicals compared to the readily ones, a model is preferred that gives a minimum of false positives without a corresponding high percentage false negatives. A combination of the BIOWIN models (BIOWIN2 or BIOWIN6) showed the highest predictive value for not-readily biodegradability. However, the highest score for overall predictivity with lowest percentage false predictions was achieved by applying BIOWIN3 (pass level 2.75) and BIOWIN6.     

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.     

取代苯胺及苯酚类化合物定量结构-生物降解相关性(QSBR)研究

采用MOPAC－AM1法计算了15种取代苯分子的三种量化参数,用QSAR程序计算了两种物化参数及一种电性参数,结合德华半径RW,对log Kb进行了回归分析,得到如下最佳方程：log Kb=0.329 pK-10.48kw-12.995应用所得QSBR模式预测了15种有机物的生物降解性,并分析了降解机理。     

External validation of structure-biodegradation relationship (SBR) models for predicting the biodegradability of xenobiotics

Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure–biodegradation relationship (SBR) and quantitative structure–biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite? includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.     

The effect of gamma radiation on biodegradability of morpholine in aqueous solution

The effect of -radiation on the aqueous solution of morpholine was studied on the basis of UV spectrum measurement, COD /chemical oxygen demand/, TOC /total organic carbon/ and STOD /short-term oxygen demand/ determination and Pitter's kinetic test of biodegradation. The biodegradability of the model solution after irradiation became substantially worse.     

Strategies for detecting ecotoxicological effects of biodegradable polymers in agricultural applications

Biodegradable is the long awaited and highly accepted property for materials (polymers) used in agricultural applications. Methods for determining biodegradability and material disintegration are established and already in use for routine analysis. Methods for analysing ecotoxic effects caused by biodegradable materials are neither established nor in routine use. In the past, biotests have been developed and optimised solely for investigations of single chemicals. Such tests are applicable even if they are not validated for the detection of undesired ecotoxicological effects deriving from biodegradation of polymers in soil. Since the biodegradation process does have an influence on the physical, chemical and biological status of the soil matrix, both biotests and chemical analysis are required in many cases. Theory, background data from method development and some results are presented.     

Theoretical trends of diffusion and reaction into tubular nano- and mesoporous structures: general physicochemical and physicomathematical modeling

A general and adaptable physicochemical model is presented to evaluate the mass transport within nanopores of mesoporous particles when the mass transport is coupled to heterogeneous kinetics occurring at active sites located onto the nanopore walls surface. The model framework encompasses almost all situations of practical interest in solutions and may be used for characterizing the kinetic rates and constants controlling the system under different sets of experimental conditions. Furthermore, it allows the delineation of simple effective parameters, which should be most useful for optimizing a given material in view of specific applications. For the sake of clarification the simplified model is presented and its results discussed by specializing it for cases where the reactions involve a simple adsorption of a target species on the nanopore immobilized sites as observed for inorganic sponges used in water decontamination. Yet it may easily be extended further to encompass a wider variety of situations where the sites immobilized onto the nanopore walls perform chemical or biochemical transformations as occur in supported catalysis in liquid solution.     

Biodegradabilities of some chain oils in groundwater as determined by the respirometric BOD OxiTop method

The respirometric BOD OxiTop method was used to monitor the biodegradation of different chain oils (mineral, rapeseed and tall oils) over 28 days in groundwater, as well as in standard conditions described by OECD 301 F. The aim of the study was to gather more information about the biodegradability of forestry oils in groundwater, as well as about the suitability of the automatic OxiTop method for biodegradation measurements. The BOD OxiTop method proved to be a precise and reliable technique for determining the biodegradations of different oils. Some comparative studies were also made using a traditional IR method in order to clarify the total oil concentrations. The results show that if biodegradation only is to be monitored, the OxiTop method is preferable. This is due to the influence of other reactions aside from biodegradation on total hydrocarbon concentrations when using the IR method.     

A collision theory-based derivation of semiempirical equations for modeling dispersive kinetics and their application to a mixed-phase crystal decomposition

In recent works, the author has shown the utility of new, semiempirical kinetic model equations for treating dispersive chemical processes ranging from slow (minute/hour time scale) solid-state phase transformations to ultrafast (femtosecond) reactions in the gas phase. These two fundamental models (one for homogeneous/deceleratory sigmoidal conversion kinetics and the other for heterogeneous/acceleratory sigmoidal kinetics; isothermal conditions), based on the assumption of a "Maxwell-Boltzmann-like" distribution of molecular activation energies, provide a novel, quantum-based interpretation of the kinetics. As an extension to previous work, it is shown here that the derivation of these dispersive kinetic equations is supported by classical collision theory (i.e., for gas-phase applications). Furthermore, the successful application of the approach to the kinetic modeling of the solid-state decomposition of a binary system, CO2.C2H2, is demonstrated. Finally, the models derived appear to explain some of the (solid-state) kinetic data collected using isoconversional techniques such as those often reported in the thermal analysis literature.     

External validation of the biodegradability prediction model CATABOL using data sets of existing and new chemicals under the Japanese Chemical Substances Control Law

External validation of the biodegradability prediction model CATABOL was conducted using test data of 338 existing chemicals and 1123 new chemicals under the Japanese Chemical Substances Control Law. CATABOL predicts that 1089 chemicals will have a BOD?<?60% while 925 (85%) actually have an observed BOD<60%. The percentage of chemicals with an observed BOD value <60% tends to increase as the predicted BOD values decrease. In contrast, 340 chemicals were predicted to have a BOD?≥?60% and 234 (69%) actually had an observed BOD?≥?60%. The prediction of poor biodegradability was more accurate than the predictions of high biodegradability. The features of chemical structures affecting CATABOL predictability were also investigated.     

External validation of the biodegradability prediction model CATABOL using data sets of existing and new chemicals under the Japanese Chemical Substances Control Law

External validation of the biodegradability prediction model CATABOL was conducted using test data of 338 existing chemicals and 1123 new chemicals under the Japanese Chemical Substances Control Law. CATABOL predicts that 1089 chemicals will have a BOD < 60% while 925 (85%) actually have an observed BOD<60%. The percentage of chemicals with an observed BOD value <60% tends to increase as the predicted BOD values decrease. In contrast, 340 chemicals were predicted to have a BOD > or = 60% and 234 (69%) actually had an observed BOD > or = 60%. The prediction of poor biodegradability was more accurate than the predictions of high biodegradability. The features of chemical structures affecting CATABOL predictability were also investigated.     

Ready Biodegradability study and insights with ultra-high-performance liquid chromatograph coupled to a quadrupole time of flight of a Metformin-based drug and of Metarecod,a natural substance-based medical device

Drugs are indispensable products with incontrovertible benefits to human health and lifestyle. However, due to their overuse and improper disposal, unwanted residues of active pharmaceutical ingredients (APIs) have been found in different compartments of the environment and now are considered as contaminants of emerging concern (CECs). Therefore, they are very likely to have a boomerang effect on human health, because they can enter into the food cycle. In the current legislation framework, one of the tests first used to evaluate biodegradation of APIs as well as chemical compounds is the ready biodegradability test (RBT). This test can be performed according to a series of protocols prepared by Organization for Economic Co-operation and Development (OECD) and usually is carried out on pure compounds. RBTs, largely used due to their relatively low cost, perceived standardization, and straightforward implementation and interpretation, are known to have a number of well-documented limitations. In this work, following a recently reported approach, we propose to improve the evaluation of the RBT results applying advanced analytical techniques based on mass spectrometry, not only to the APIs but also to complex formulated products, as the biodegradability can potentially be affected by the formulation. We evaluated the ready biodegradability of two therapeutic products, Product A —a drug based on Metformin—and Product B —Metarecod a natural substance-based medical device—through the acquisition of the fingerprint by ultra-high-performance chromatograph coupled to a quadrupole time of flight (UHPLC-qToF) of samples coming from the RBT OECD 301F. Untargeted and targeted evaluation confirmed the different behavior of the two products during the respirometry-manometric test, which showed a difficulty of the Metformin-based drug to come back in the life cycle, whereas Metarecod resulted ready biodegradable. The positive results of this research will hopefully be useful in the future for a better evaluation of the risk/benefit ratio of APIs extended to the environment.     

Using chemical categories to fill data gaps in hazard assessment

Hazard assessments of chemicals have been limited by the availability of test data and the time needed to evaluate the test data. While available data may be inadequate for the majority of industrial chemicals, the body of existing knowledge for most hazards is large enough to permit reliable estimates to be made for untested chemicals without additional animal testing. We provide a summary of the growing use by regulatory agencies of the chemical categories approach, which groups chemicals based on their similar toxicological behaviour and fills in the data gaps in animal test data such as genotoxicity and aquatic toxicity. Although the categories approach may be distinguished from the use of quantitative structure–activity relationships (QSARs) for specific hazard endpoints, robust chemical categories are founded on quantifying the chemical structure with parameters that control chemical behaviour in conventional hazard assessment. The dissemination of the QSAR Application Toolbox by the Organisation for Economic Cooperation and Development (OECD) is an effort to facilitate the use of the categories approach and reduce the need for additional animal testing.     

Experimental verification of structural alerts for the protein binding of cyclic compounds acting as Michael acceptors

This study outlines how a combination of and in vitro data can be used to define the applicability domain of selected structural alerts within the protein binding profilers of the Organisation for Economic Co-operation (OECD) Quantitative Structure–Activity Relationship (QSAR) Toolbox. Thirty chemicals containing a cyclic moiety were profiled for reactivity using the OECD and Optimised Approach based on Structural Indices Set (OASIS) protein binding profilers. The profiling results identified 22 of the chemicals as being reactive towards proteins. Analysis of the experimentally data showed 19 of these chemicals to be reactive. Subsequent analysis allowed refinements to be suggested to improve the applicability domain of the structural alerts investigated. The accurate definition of the applicability domain for structural alerts within in silico profilers is important due to their use in chemical category in predictive and regulatory toxicology.     

CATALOGIC 301C model – validation and improvement

In Europe, REACH legislation encourages the use of alternative in silico methods such as (Q)SAR models. According to the recent progress of Chemical Substances Control Law (CSCL) in Japan, (Q)SAR predictions are also utilized as supporting evidence for the assessment of bioaccumulation potential of chemicals along with read across. Currently, the effective use of read across and QSARs is examined for other hazards, including biodegradability. This paper describes the results of external validation and improvement of CATALOGIC 301C model based on more than 1000 tested new chemical substances of the publication schedule under CSCL. CATALOGIC 301C model meets all REACH requirements to be used for biodegradability assessment. The model formalism built on scientific understanding for the microbial degradation of chemicals has a well-defined and transparent applicability domain. The model predictions are adequate for the evaluation of the ready degradability of chemicals.