Investigation on the relationship between bioconcentration factor and distribution coefficient based on class-based compounds: The factors that affect bioconcentration

Fragments quantum descriptors in classification of bio-accumulative compounds

The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended databases. A number of compounds with results from quantum-chemical calculations conducted with Psi4 quantum chemistry package was also added to the quantum properties database. Classification results are compared with a baseline of random guesses and predictions obtained with the traditional RDKit generated molecular descriptors. Chosen classification metrics show that results obtained with fragments quantum descriptors fall between results from baseline and those provided by molecular descriptors widely applied in cheminformatics. According to the results, the implementation of principal component analysis, causes a drop in categorization metrics.

Microalgal-based bioremediation of emerging contaminants: Mechanisms and challenges

Emerging contaminants (ECs) in different ecosystems have consistently been acknowledged as a global issue due to toxicity, human health implications, and potential role in generating and disseminating antimicrobial resistance. The existing wastewater treatment system is incompetent at eliminating ECs since the effluent water contains significant concentrations of ECs, viz., antibiotics (0.03-13.0 μg L-1), paracetamol (50 μg L-1), and many others in varying concentrations. Microalgae are considered as a prospective and sustainable candidate for mitigating of ECs owing to some peculiar features. In addition, the microalgal-based processes also offer cost and energy-efficient solutions for the bioremediation of ECs than conventional treatment systems. It is pertinent that, microalgal-based processes also provides waste valorization benefits as microalgal biomass obtained after ECs treatment can be potentially applied to generate biofuels. Moreover, microalgae can effectively utilize alternative metabolic (cometabolism) routes for enhanced degradation of ECs. Additionally, the ECs removal via the microalgal biodegradation route is highly promising as it can transform the ECs into less toxic compounds. The present review comprehensively discusses different mechanisms involved in removing ECs and various factors that affect their removal. Also, the technoeconomic feasibility of microalgae than other conventional wastewater treatment methods is summarised. The review also highlighted the different molecular and genetic tools that can augment the activity and robustness of microalgae for better removal of organic contaminants. Finally, we have summarised the challenges and future research required towards microalgal-based bioremediation of emerging contaminants (ECs) as a holistic approach.

A Comprehensive Evaluation System for the Stabilization Effect of Heavy Metal-Contaminated Soil Based on Analytic Hierarchy Process

Stabilization technology is widely used in the remediation of heavy metal-contaminated farmland soil. However, the evaluation method for the remediation effect is not satisfactory. To scientifically evaluate the remediation effect, this study constructed a comprehensive evaluation system by bibliometric analysis and an analytic hierarchy process (AHP). Ultimately, 16 indicators were selected from three aspects of the soil, crops, and amendment. The 16 indicators are divided into three groups, namely indicators I that can be evaluated according to the national standards of China, indicators II that can be evaluated according to the classification management of farmland and Indicators III that are the dynamic change indicators without an evaluation criterion. Comprehensive scores for 16 indicators were calculated using three response models, respectively. According to the difference between the scores before and after the remediation, the remediation effect is divided into five levels, which are excellent, good, qualified, poor, and very poor. This study provides a theoretical basis and insightful information for a farmland pollution remediation and a sustainable utilization.

Microalgae-based removal of pollutants from wastewaters: Occurrence, toxicity and circular economy

The natural and anthropogenic sources of water bodies are contaminated with diverse categories of pollutants such as antibiotics, pharmaceuticals, pesticides, heavy metals, organic compounds, and other industrial chemicals. Depending on the type and the origin of the pollutants, the degree of contamination can be categorized into lower to higher concentrations. Therefore, the removal of hazardous chemicals from the environment is an important aspect. The physical, chemical and biological approaches have been developed and implemented to treat wastewaters. The microbial and algal treatment methods have emerged as a growing field due to their eco-friendly and sustainable approach. Particularly, microalgae emerged as a potential organism for the treatment of contaminated water bodies. The microalgae of the genera Chlorella, Anabaena, Ankistrodesmus, Aphanizomenon, Arthrospira, Botryococcus, Chlamydomonas, Chlorogloeopsis, Dunaliella, Haematococcus, Isochrysis, Nannochloropsis, Porphyridium, Synechococcus, Scenedesmus, and Spirulina reported for the wastewater treatment and biomass production. Microalgae have the potential for adsorption, bioaccumulation, and biodegradation. The microalgal strains can mitigate the hazardous chemicals via their diverse cellular mechanisms. Applications of the microalgae strains were found to be effective for sustainable developments and circular economy due to the production of biomass with the utilization of pollutants.

Environmental health and risk assessment metrics with special mention to biotransfer, bioaccumulation and biomagnification of environmental pollutants

The environment pollutants, which are landed up in environment because of human activities like urbanization, mining and industrializations, affects human health, plants and animals. The living organisms present in environment are constantly affected by the toxic pollutants through direct contact or bioaccumulation of chemicals from the environment. The toxic and hazardous pollutants are easily transferred to different environmental matrices like land, air and water bodies such as surface and ground waters. This comprehensive review deeply discusses the routes and causes of different environmental pollutants along with their toxicity, impact, occurrences and fate in the environment. Environment health and risk assessment tools that are used to evaluate the harmfulness, exposure of living organisms to pollutants and the amount of pollutant accumulated are explained with help of bio-kinetic models. Biotransfer, toxicity factor, biomagnification and bioaccumulation of different pollutants in the air, water and marine ecosystems are critically addressed. Thus, the presented survey would be collection of correlations those addresses the factors involved in assessing the environmental health and risk impacts of distinct environmental pollutants.

Discrimination of active and inactive substances in cytotoxicity based on Tox21 10K compound library: Structure alert and mode of action

In vitro cytotoxicity assay is an ideal alternative method for the in vivo toxicity in the risk assessment of pollutants in environment. However, modes of action (MOAs) of cytotoxicity have not been investigated for a wide range of compounds. In this paper, binomial and recursive partitioning analysis were carried out between the cytotoxicity and molecular descriptors for 8981 compounds. The results showed that cytotoxicity is strongly related to the chemical hydrophobicity and excess molar refraction, indicating the bio-uptake and chemical-receptor interaction through π and n electron pair play important roles in the cytotoxicity. The decision tree derived from recursive partitioning analysis revealed that the studied compounds could be divided into 25 groups and their structural characteristics could be used as structure alert to identify active and inactive compounds in cytotoxicity. The descriptors used in the decision tree revealed that chemical ionization and bioavailability could affect the cytotoxicity for ionizable and highly hydrophobic compounds. Comparison of MOAs based on Verhaar's classification scheme showed that many inert or less inert compounds were inactive substance, and many reactive or specifically-acting compounds were active substances in the cytotoxicity. In vitro toxicity assay instead of in vivo toxicity assay can be used in the environmental hazard and risk assessment of organic pollutants. The descriptors used in the binomial equation and decision tree reveal that chemical hydrophobicity, ionization and solubility play very important roles for identification of active and inactive compounds. The results obtained in this paper are valuable for understanding the modes of action in cytotoxicity and in vivo-in vitro toxicity relationship.

In silico local QSAR modeling of bioconcentration factor of organophosphate pesticides

The persistent and accumulative nature of the pesticide of indiscriminate use emerged as ecotoxicological hazards. The bioconcentration factor (BCF) is one of the key elements for environmental assessments of the aquatic compartment. Limitations of prediction accuracy of global model facilitate the use of local predictive models in toxicity modeling of emerging compounds. The BCF data of diverse organophosphate (n = 55) was collected from the Pesticide Properties Database and used as a model data set in the present study to explore physicochemical properties and structural alert concerning BCF. The structures were downloaded from Pubchem, ChemSpider database. Two splitting techniques (biological sorting and structure-based) were used to divide the whole dataset into training and test set compounds. The QSAR study was carried out with two-dimensional descriptors (2D) calculated from PaDEL by applying genetic algorithm (GA) as chemometric tools using QSARINS software. The models were statistically robust enough both internally as well as externally (Q2: 0.709-0.722, Q2 Ext: 0.717-0.903, CCC: 0.857-0.880). Overall molecular mass, presence of fused, and heterocyclic ring with electron-withdrawing groups affect the BCF value. The developed models reflected extended applicability domain (AD) and reliable predictions than the reported models for the studied chemical class. Finally, predictions of unknown organophosphate pesticides and the toxic nature of unknown organophosphate pesticides were commented on. These findings may be useful for the scientific community in prioritizing high potential pesticides of organophosphate class.

Relationship among the acute toxicity, critical body residue, and bioconcentration of ortho-dinitrobenzene in zebrafish (Danio rerio) based on toxicokinetics

The internal critical concentration represented by the critical body residue (CBR) is an ideal indicator for reflecting the toxicity of a chemical. Although some authors have realized that the CBR₅₀ can be calculated from the LC₅₀ via the bioconcentration factor (BCF), the effects of exposure time and exposure concentration on the relationship between the LC₅₀ and CBR₅₀ have not been investigated to date. In this paper, the LC₅₀ and CBR₅₀ of ortho-dinitrobenzene in zebrafish were experimentally determined and their relationship was investigated. The results showed that ortho-dinitrobenzene exhibited excess toxicity and cannot completely be identified as a reactive compound based on toxic ratio. Comparison of the measured CBR₅₀ and the CBR₅₀ calculated from the LC₅₀ via the BCF showed that there was a 0.46 log unit difference. Investigation of the relationship between the concentration in fish calculated by the toxicokinetic model and exposure time showed that the bio-uptake of fish was fast and reached a steady state in the toxicity test, indicating that the difference in CBR₅₀ values could not be attributed to the different exposure times used in toxicity and BCF assays. On the other hand, investigation of the measured bioconcentration ratio (BCR) showed that the BCR (or BCF_app) decreased with increasing exposure concentration. Compared with the CBR₅₀ calculated from the LC₅₀ via the BCF, the CBR₅₀ calculated from the LC₅₀ via the BCF_app is close to the measured CBR₅₀, suggesting that the difference in CBR₅₀ values is attributed to the different exposure concentrations used in the BCF and toxicity assays.

Multiple Bioassays and Targeted and Nontargeted Analyses to Characterize Potential Toxicological Effects Associated with Sediments of Masan Bay: Focusing on AhR-Mediated Potency

An enhanced, multiple lines of evidence approach was applied to assess potential toxicological effects associated with polluted sediments. Two in vitro bioassays (H4IIE-luc and Vibrio fischeri) and three in vivo bioassays (microalgae: Isochrysis galbana and Phaeodactylum tricornutum; zebrafish embryo: Danio rerio) were applied. To identify causative chemicals in samples, targeted analyses (polycyclic aromatic hydrocarbons (PAHs), styrene oligomers (SOs), and alkylphenols) and nontargeted full-scan screening analyses (FSA; GC- and LC-QTOFMS) were performed. First, great AhR-mediated potencies were observed in midpolar and polar fractions of sediment extracts, but known and previously characterized AhR agonists, including PAHs and SOs could not fully explain the total potencies of samples. Enoxolone was identified as a novel AhR agonist in a highly potent sediment fraction by use of FSA. Enoxolone has a relative potency of 0.13 compared to benzo[a]pyrene (1.0) in the H4IIE-luc bioassay. Nonylphenols associated with membrane damage that influenced the viability of the microalgae were also observed. Finally, inhibitions of bioluminescence of V. fischeri and lethality of D. rerio embryos were strongly related to nonpolar compounds. Overall, the present work addressed assay- and end point-specific variations and sensitivities for potential toxicities of mixture samples, warranting a significant utility of the "multiple lines of evidence" approach in ecological risk assessment.

Bioremediation of water containing pesticides by microalgae: Mechanisms, methods, and prospects for future research

The application of pesticides reduces the loss of crops while simultaneously increasing crop productivity. However, the frequent use of pesticides can cause serious environmental problems due to their high accumulative and persistent nature. Recently, microalgae technology has received considerable success in the efficient treatment of pesticides pollution. In this review, the metabolic mechanisms responsible for the removal of pesticides are summarized based on previous studies. Different methods used to enhance the ability of microalgae to remove pesticides are critically evaluated. The recycling of microalgae biomass after wastewater treatment for biochar preparation and biodiesel production using the biorefinery approach is also introduced. Furthermore, we present potential future research directions to highlight the prospects of microalgae research in the removal of pesticides along with the production of value-added products.

Detecting the bioaccumulation patterns of chemicals through data-driven approaches

This work investigates the bioaccumulation patterns of 168 organic chemicals in fish, by comparing their bioconcentration factor (BCF), biomagnification factor (BMF) and octanol-water partitioning coefficient (K_OW). It aims to gain insights on the relationships between dietary and non-dietary bioaccumulation in aquatic environment, on the effectiveness of K_OW and BCF to detect compounds that bioaccumulate through diet, as well as to detect the presence of structure-related bioaccumulation patterns. A linear relationship between logBMF and logK_OW was observed (logBMF = 1.14·logBCF - 6.20) up to logK_OW ≈ 4, as well as between logBMF and logBCF (logBMF = 0.96·logBCF - 4.06) up to a logBCF ≈ 5. 10% of compounds do not satisfy the linear BCF-BMF relationship. The deviations from such linear relationships were further investigated with the aid of a self-organizing map and canonical correlation analysis, which allowed us to shed light on some structure-related patterns. Finally, the usage of K_OW- and BCF-based thresholds to detect compounds that accumulate through diet led to many false positives (47%-91% for K_OW), and a moderate number of false negatives (up to 5% for BCF). These results corroborate the need of using the experimental BMF for hazard assessment practices, as well as of developing computational tools for BMF prediction.

Estimation of physicochemical properties of 2-ethylhexyl-4-methoxycinnamate (EHMC) degradation products and their toxicological evaluation

The organic UV filters, commonly used in personal protection products, are of concern because of their potential risk to aquatic ecosystems and living organisms. One of UV filters is ethylhexyl-4-methoxycinnamate (EHMC) acid. Studies have shown that, in the presence of oxidizing and chlorinating factors, EHMC forms a series of products with different properties than the substrate. In this study, the toxicities of EHMC and its transformation/degradation products formed under the influence of NaOCl/UV and H₂O₂/UV systems in the water medium were tested using Microtox® bioassay and by observation of mortality of juvenile crustaceans Daphnia magna and Artemia Salina. We have observed that oxidation and chlorination products of EHMC show significantly higher toxicity than EHMC alone. The toxicity of chemicals is related to their physicochemical characteristic such as lipophilicity and substituent groups. With the increase in lipophilicity of products, expressed as log K_OW, the toxicity (EC₅₀) increases. On the basis of physicochemical properties such as vapour pressure (VP), solubility (S), octanol-water partition coefficient (K_OW), bioconcentration factor (BCF) and half-lives, the overall persistence (P_OV) and long-range transport potential (LRTP) of all the products and EHMC were calculated. It was shown that the most persistent and traveling on the long distances in environment are methoxyphenol chloroderivatives, then methoxybenzene chloroderivatives, EHMC chloroderivatives, methoxybenzaldehyde chloroderivatives and methoxycinnamate acid chloroderivatives. These compounds are also characterised by high toxicity.

Liquid chromatography-mass spectrometry method for evaluating the dissipation dynamics of cyromazine and its metabolite in Agaricus bisporus and dietary risk assessment

Providing guidance on the reasonable use of pesticide in agricultural production is of particular importance for ensuring food safety. In the present study, a field trial was performed to study the dissipation and accumulative pattern of cyromazine (CA) and its metabolite in Agaricus bisporus (A. bisporus) cultivation. An ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was first developed and validated for the determination of CA and melamine (MEL) in the casing soil and fruiting body. During the cultivation period, the dissipation rates of CA in the casing soil were between 51.57 and 63.48% at three dose groups. The fruiting body presented higher accumulation ability for MEL compared with CA. The terminal residues of MEL never exceeded the maximum residue limits (MRLs) in food. In addition, the intake health risk from the CA and MEL residues in the fruiting body were negligible to humans. This study will help to provide valuable guidance on the application strategies of CA in A. bisporus cultivation.

High bioconcentration of titanium dioxide nanoparticles in Daphnia magna determined by kinetic approach

The environmental risk assessments of titanium dioxide nanoparticles (TiO2 NPs) have drawn wide attention and one of the required critical information is the bioconcentration potentials of these nanoparticles in aquatic organisms. In the present study, the bioconcentration of six commercially available TiO2 NPs with different sizes and surface properties were quantified in a freshwater cladoceran Daphnia magna using kinetic modeling approach. We first calculated the uptake rate constant (ku) and depuration rate constant (ke) of TiO2 NPs and then employed a first-order kinetic model to predict the bioconcentration factors (BCF) at different TiO2 NPs concentrations. Both the ku and ke of TiO2 NPs were significantly affected by the exposure concentration and the nanoparticle property. The predicted BCF values in D. magna of six TiO2 NPs ranged from 2.40×10(5)L/kg to 1.52×10(6)L/kg, and had no clear correlation with the exposure concentration. Large nominal size resulted in a lower BCF of TiO2 NPs at lower exposure concentration. Higher hydrophobicity and Al(OH)3 coating also resulted in a higher BCF. All the six TiO2 NPs in this study were therefore considered very bioaccumulative. More attention should be paid to bioconcentration in the environmental risk assessments of TiO2 NPs, and the physicochemical properties of TiO2 NPs should be taken into account.

Investigating the mechanisms of bioconcentration through QSAR classification trees

This paper proposes a scheme to predict whether a compound (1) is mainly stored within lipid tissues, (2) has additional storage sites (e.g., proteins), or (3) is metabolized/eliminated with a reduced bioconcentration. The approach is based on two validated QSAR (Quantitative Structure-Activity Relationship) trees, whose salient features are: (a) descriptor interpretability and (b) simplicity. Trees were developed for 779 organic compounds, the TGD approach was used to quantify the lipid-driven bioconcentration, and a refined machine-learning optimization procedure was applied. We focused on molecular descriptor interpretation, which allowed us to gather new mechanistic insights into the bioconcentration mechanisms.

Comparison of Toxicities to Vibrio fischeri and Fish Based on Discrimination of Excess Toxicity from Baseline Level

Investigations on the relationship of toxicities between species play an important role in the understanding of toxic mechanisms to environmental organisms. In this paper, the toxicity data of 949 chemicals to fish and 1470 chemicals to V. fischeri were used to investigate the modes of action (MOAs) between species. The results show that although there is a positive interspecies correlation, the relationship is poor. Analysis on the excess toxicity calculated from toxic ratios (TR) shows that many chemicals have close toxicities and share the same MOAs between the two species. Linear relationships between the toxicities and octanol/water partition coefficient (log KOW) for baseline and less inert compounds indicate that the internal critical concentrations (CBRs) approach a constant both to fish and V. fischeri for neutral hydrophobic compounds. These compounds share the same toxic mechanisms and bio-uptake processes between species. On the other hand, some hydrophilic compounds exhibit different toxic effects with greatly different log TR values between V. fischeri and fish species. These hydrophilic compounds were identified as reactive MOAs to V. fischeri, but not to fish. The interspecies correlation is improved by adding a hydrophobic descriptor into the correlation equation. This indicates that the differences in the toxic ratios between fish and V. fischeri for these hydrophilic compounds can be partly attributed to the differences of bioconcentration between the two species, rather than the differences of reactivity with the target macromolecules. These hydrophilic compounds may more easily pass through the cell membrane of V. fischeri than the gill and skin of fish, react with the target macromolecules and exhibit excess toxicity. The compounds with log KOW > 7 exhibiting very low toxicity (log TR < -1) to both species indicate that the bioconcentration potential of a chemical plays a very important role in the identification of excess toxicity and MOAs.

Influences of binding to dissolved organic matter on hydrophobic organic compounds in a multi-contaminant system: Coefficients, mechanisms and ecological risks

The complexation flocculation (CF) method was successfully employed to identify binding coefficients (Kdoc) of specific organic contaminants to dissolved organic matter (DOM, often indicated by dissolved organic carbon, DOC) in a multi-contaminant hydrophobic organic contaminant (HOC) system. Kdoc values were obtained for most of the evaluated 33 HOCs, indicating the feasibility and applicability of the CF method in a multi-contaminant system. Significant positive correlations were observed between binding coefficients and octanol-water partition coefficients (Kow) for organic halogen compounds, such as polybrominated diphenyl ethers (PBDEs) (R(2) = 0.95, p < 0.05) and organic chlorine pesticides (OCPs) (methoxychlor excluded, R(2) = 0.82, p < 0.05). The positive correlations identified between the lgKdoc and lgBCF (bioconcentration factor) for PBDEs and OCPs, as well as the negative correlation observed for polycyclic aromatic hydrocarbons (PAHs), indicated that different binding or partition mechanisms between PAHs and organic halogen compounds exist. These differences further result in discriminative competition partitions of HOCs between DOM and organisms. Assuming that only freely dissolved HOCs are bioconcentrative, the results of DOM-influenced bioconcentration factor (BCFDOM) and DOM-influenced lowest observed effect level (LOELDOM) indicate that the ecological risk of HOCs is decreased by DOM.

Comparison between bioconcentration factor (BCF) data provided by industry to the European Chemicals Agency (ECHA) and data derived from QSAR models

The bioconcentration factor (BCF) is the ratio of the concentration of a chemical in an organism to the concentration in the surrounding environment at steady state. It is a valuable indicator of the bioaccumulation potential of a substance. BCF is an essential environmental property required for regulatory purposes within the Registration, Evaluation, Authorization and restriction of Chemicals (REACH) and Globally Harmonized System (GHS) regulations. In silico models for predicting BCF can facilitate the risk assessment for aquatic toxicology and reduce the cost and number of animals used. The aim of the present study was to examine the correlation of BCF data derived from the dossiers of registered chemicals submitted to the European Chemical Agency (ECHA) with the results of a battery of Quantitative Structure-Activity Relationship (QSAR). After data pruning, statistical analysis was performed using the predictions of the selected models. Results in terms of R(2) had low rating around 0.5 for the pruned dataset. The use of the model applicability domain index (ADI) led to an improvement of the performance for compounds falling within it. The variability of the experimental data and the use of different parameters to define the applicability domain can influence the performance of each model. All available information should be adapted to the requirements of the regulation to obtain a safe decision.

Comparison of toxicity of class-based organic chemicals to algae and fish based on discrimination of excess toxicity from baseline level

Toxicity data to fish and algae were used to investigate excess toxicity between species. Results show that chemicals exhibiting excess toxicity to fish also show excess toxicity to algae for most of the compounds. This indicates that they share the same mode of action between species. Similar relationships between logKOW and toxicities to fish and algae for baseline and less inert compounds suggest that they have similar critical body residues in the two species. Differences in excess toxicity for some compounds suggest that there is a difference of physiological structure and metabolism between fish and algae. Some reactive compounds (e.g. polyamines) exhibit greater toxic effects for algae than those for fish because of relatively low bio-uptake potential of these hydrophilic compounds in fish as compared with that in algae. Esters exhibiting greater toxicity in fish than that in algae indicate that metabolism can affect the discrimination of excess toxicity from baseline level. Algae growth inhibition is a very good surrogate for fish lethality. This is not only because overall toxicity sensitivity to algae is greater than that to fish, but also the excess toxicity calculated from algal toxicity can better reflect reactivity of compounds with target molecules than fish toxicity.

The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals

Quantitative structure-activity relationships (QSARs) were developed to predict the Michaelis-Menten constant (Km) and the maximum reaction rate (Vmax) of xenobiotics metabolised by four enzyme classes in mammalian livers: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP). Metabolic constants were gathered from the literature and a genetic algorithm was employed to select at most six predictors from a pool of over 2000 potential molecular descriptors using two-thirds of the xenobiotics in each enzyme class. The resulting multiple linear models were cross-validated using the remaining one-third of the compounds. The explained variances (R(2)adj) of the QSARs were between 50% and 80% and the predictive abilities (R(2)ext) between 50% and 60%, except for the Vmax QSAR of FMO with both R(2)adj and R(2)ext less than 30%. The Vmax values of FMO were independent of substrate chemical structure because the rate-limiting step of its catalytic cycle occurs before compound oxidation. For the other enzymes, Vmax was predominantly determined by functional groups or fragments and electronic properties because of the strong and chemical-specific interactions involved in the metabolic reactions. The most relevant predictors for Km were functional groups or fragments for the enzymes metabolising specific compounds (ADH, ALDH and FMO) and size and shape properties for CYP, likely because of the broad substrate specificity of CYP enzymes. The present study can be helpful to predict the Km and Vmax of four important oxidising enzymes in mammals and better understand the underlying principles of chemical transformation by liver enzymes.