Physico-chemical characteristics and quantitative structure-activity relationships of PCBs by Patrik Andersson Akademisk avhandling Som med tillstånd av rektorsämbetet vid Umeå universitet för erhållande av Filosofie Doktorsexamen vid Teknisk-naturvetenskapliga fakulteten i Umeå, framlägges till offentlig granskning vid Kemiska Institutionen, hörsal KB3B1 i KBC, fredagen den 26 maj, 2000, kl. 13.00. Fakultetsopponent: Professor Stephen Safe, Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA. ISBN 91-7191-838-8 Copyright © 2000 by Patrik Andersson Printed in Sweden by Solfjädern Offset AB, Umeå 2000 Title Physico-chemical characteristics and quantitative structure-activity relationships of PCBs Author Patrik Andersson, Department of Chemistry, Environmental Chemistry, Umeå University, SE-901 87 Umeå, Sweden. Abstract The polychlorinated biphenyls (PCBs) comprise a group of 209 congeners varying in the number of chlorine atoms and substitution patterns. These compounds tend to be biomagnified in foodwebs and have been shown to induce an array of effects in exposed organisms. The structural characteristics of the PCBs influence their potency as well as mechanism of action. In order to assess the biological potency of these compounds a multi-step quantitative structure-activity relationship (QSAR) procedure was used in the project described in this thesis. The ultraviolet absorption (UV) spectra were measured for all 209 PCBs, and digitised for use as physico-chemical descriptors. Interpretations of the spectra using principal component analysis (PCA) showed the number of ortho chlorine atoms and para-para substitution patterns to be significant. Additional physico-chemical descriptors were derived from semi-empirical calculations. These included various molecular energies, the ionisation potential, electron affinity, dipole moments, and the internal barrier of rotation. The internal barrier of rotation was especially useful for describing the conformation of the PCBs on a continuous scale. In total 52 physico-chemical descriptors were compiled and analysed by PCA for the tetra- to hepta-chlorinated congeners. The structural variation within these compounds was condensed into four principal properties derived from a PCA for use as design variables in a statistical design to select congeners representative for these homologue-groups. The 20 selected PCBs have been applied to study structure-specific biochemical responses in a number of bioassays, and to study the biomagnification of the PCBs in various fish species. QSARs were established using partial least squares projections to latent structures (PLS) for the PCBs potency to inhibit intercellular communication, activate respiratory burst, inhibit dopamine uptake in synaptic vesicles, compete with estradiol for binding to estrogen receptors, and induce cytochrome P4501A (CYP1A) related activities. By the systematic use of the designed set of PCBs the biological potency was screened over the chemical domain of the class of compounds. Further, sub-regions of highly potent PCBs were identified for each response measured. For risk assessment of the PCBs potency to induce dioxin-like activities the predicted induction potencies (PIPs) were calculated. In addition, two sets of PCBs were presented that specifically represent congeners of environmental relevance in combination with predicted potency to induce estrogenic and CYP1A related activities. Keywords polychlorinated biphenyls, PCBs, physico-chemical properties, statistical design, multivariate, PCA, PLS, biomagnification, BMF, bioassay, CYP1A, SAR, QSAR, REPs, risk assessment ISBN 91-7191-838-8 Contents 1. List of Papers....................................................................................................................................ii 2. Abbreviations..................................................................................................................................iii 3. Introduction.....................................................................................................................................1 3.1 Production and use...................................................................................................................2 3.2 Physico-chemical properties of individual PCBs.....................................................................3 3.3 Environmental occurrence........................................................................................................5 3.4 Transport and fate....................................................................................................................6 3.5 Metabolism...............................................................................................................................7 3.6 Human health effects................................................................................................................9 3.7 The TEF concept....................................................................................................................10 3.8 Quantitative structure-activity relationships..........................................................................11 3.9 Aims and scope.......................................................................................................................12 4. Multivariate methods and statistical design.................................................................................14 4.1 Principal component analysis.................................................................................................14 4.2 Partial least squares projections to latent structures..............................................................15 4.3 Statistical design......................................................................................................................16 5. Physico-chemical descriptors and characteristics...........................................................................18 5.1 Semi-empirical descriptors......................................................................................................20 5.1.1 Internal barrier of rotation.............................................................................................22 5.2 Empirical descriptors..............................................................................................................24 5.2.1 Ultraviolet absorption spectra........................................................................................25 5.3 Physico-chemical descriptors - an update..............................................................................26 5.4 Physico-chemical characterisation of PCBs............................................................................27 6. Selection for screening and optimisation......................................................................................29 7. SAR and QSAR modelling............................................................................................................34 7.1 QSAR modelling - the biological activities............................................................................35 7.1.1 Biomagnification............................................................................................................36 7.1.2 Intercellular communication..........................................................................................38 7.1.3 Dopamine uptake...........................................................................................................39 7.1.4 Respiratory burst............................................................................................................39 7.1.5 Endocrine effects............................................................................................................40 7.1.6 CYP1A related activities.................................................................................................43 7.2 QSAR modelling - the screening phase.................................................................................45 7.2.1 Intercellular communication..........................................................................................45 7.2.2 Dopamine uptake...........................................................................................................46 7.2.3 Respiratory burst............................................................................................................47 7.2.4 Competitive binding to ER...........................................................................................47 7.2.5 CYP1A related activities.................................................................................................48 7.3 QSAR modelling - the optimisation phase..........................................................................50 7.4 Summary.................................................................................................................................53 8. Concluding remarks and future perspectives...............................................................................55 9. Acknowledgements........................................................................................................................58 10. References......................................................................................................................................59 i 1. List of Papers This thesis is based on the following papers, which will be referred to in the text by their roman numerals. I. Andersson P, Haglund P, Rappe C and Tysklind M. “Ultraviolet absorption characteristics and calculated semi-empirical parameters as chemical descriptors in multivariate modelling of polychlorinated biphenyls”. J Chemometrics 10:171-185, 1996. II. Andersson P.L, Haglund P and Tysklind M. “The Internal Barriers of Rotation for the 209 Polychlorinated Biphenyls”. Environ Sci & Pollut Res 4:75-81, 1997. III. Andersson P.L, Haglund P and Tysklind M. “Ultraviolet absorption characteristics of all 209 polychlorinated biphenyls evaluated by principal component analysis”. Fresenius J Anal Chem 357:1088-1092, 1997. IV. Tysklind M, Andersson P, Haglund P, van Bavel B and Rappe C. “Selection of polychlorinated biphenyls for use in quantitative structure-activity modelling”. SAR & QSAR in Environ Research 4:11- 19, 1995. V. Andersson P.L, Berg A.H, Bjerselius R, Norrgren L, Olsson PE, Örn S and Tysklind M. “Uptake and elimination of selected PCBs in zebra fish, three-spined stickleback and arctic char after three different routes of exposure”. Submitted to Arch Environ Contam Toxicol 2000. VI. Andersson P.L, van der Burght A.S.A.M, van den Berg M and Tysklind M. ”Multivariate modeling of PCB-induced CYP1A activity in hepatocytes from three different species: Ranking scales and species differences”. Environ Toxicol Chem 19:1454-1463, 2000. ii 2. Abbreviations AM1 Austin Model 1 BMF Biomagnification factor CYP Cytochrome P540 DDT Dichlorodiphenyl trichloroethane E2 17b -estradiol EC Effective concentration for 50% of maximal effect 50 ER Estrogen receptor EROD Ethoxyresorufin-O-deethylase Erot Internal barrier of rotation GC Gas chromatography GJIC Gap junction intercellular communication IC Effective concentration for 50% of maximal inhibition 50 Kow Octanol-water partition coefficient MCF-7 Human breast cancer cells MROD Methoxyresorufin-O-demethylase OH-PCB Hydroxylated polychlorinated biphenyl PC Principal component PCA Principal component analysis PCB Polychlorinated biphenyl PCDD Polychlorinated dibenzo-p-dioxins PCDF Polychlorinated dibenzofurans PCN Polychlorinated naphthalene PCQ Polychlorinated quaterphenyl PIP Predicted induction potency PLS Partial least squares projections to latent structures POP Persistent organic pollutant Q2 Cross-validated explained variance QSAR Quantitative structure-activity relationship REP Relative effect potency RMSEP Root mean squared error of predictions R2Y Explained variance of the dependent variable SAR Structure-activity relationship TCDD Tetrachlorinated dibenzo-p-dioxins TEF Toxic equivalency factor TEQ Toxic equivalent concentration UNEP United Nations Environmental Programme UV Ultraviolet absorption spectra iii iv Introduction 3. Introduction In recent years, the use of quantitative structure-activity relationships (QSARs) to predict the fate, persistence, and biological effects of environmental contaminants has increased. QSAR approaches including multivariate data analysis in combination with statistical design have become extensively used. Using multivariate data analysis many potentially relevant property descriptors and biological activity measurements can be handled simultaneously. In environmental chemistry this approach has been successful since investigated contaminants often include many congeners with similar structural characteristics and modes of biological action. In the work described in this thesis, statistical design was used to select training and validation sets and multivariate techniques were used to model QSARs concerning various properties of the polychlorinated biphenyls (PCBs). Cl n 3 2 2' 3' 4 4'para 5 6 6' 5' ortho meta Figure 1. General structural formulae and substitution positions of the PCBs. The PCBs comprise a group of 209 structurally different congeners with the empirical formula C H Cl (n=1-10; see Figure 1). The environmental 12 10-n n occurrence of PCBs was first reported in 1966 by Jensen, who found extremely high levels of PCBs in a white-tailed sea eagle found dead in the Stockholm archipelago. Today, PCBs can be found in all environmental compartments from the bottoms of the oceans to the aerial polar regions. The PCBs are spread into the environment from dumps, landfills, combustion processes, and from their use in various open and closed systems. They are lipophilic and enriched in adipose tissues of predators, mainly through consumption of contaminated food. The PCBs have also been shown to cause a multitude of toxic responses in wildlife and humans (Giesy and Kannan 1998; Safe 1994, van den Berg et al. 1998). The toxic effects of the PCBs were brought to public awareness by the Yusho incident in Japan 1968, where in a sudden epidemic in Western Japan, more than 1800 persons were injured due to consumption of contaminated rice oil (Kuratsune 1996). In Sweden and many other industrial countries, the production and use of PCBs have been strictly restricted since the 1970s. 1 Introduction The United Nations Environmental Programme (UNEP) has established a list of 12 classes of persistent organic pollutants, including the PCBs, along with substances such as the polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), dichlorodiphenyl trichloroethane (DDT), toxaphene, and dieldrin (UNEP report 1998). These substances are listed for global priority action to eliminate discharges, emissions, and losses. 3.1 Production and use The commercial production of PCBs started in the late 1920s and dropped dramatically during the 1970s due to scientific and public concern. The total production of PCBs has been estimated at 1.5 million tonnes (de Voogt and Brinkman 1989). The Monsanto Industrial Chemicals Co. (St. Louis, Missouri, USA) was one of the largest producers and sold mixtures of PCBs under the name Aroclor until 1977. Trade names of other producers are Kanechlor (Kanegafuchi Chemicals Co., Japan), Clophen (Bayer A.G., Germany), and Fenclor (Caffaro, Italy). The production of PCBs involves batch chlorination of biphenyl and the congener pattern in the product is principally determined by the reaction time and the amount of chlorine. More than 140 congeners can be separated from the technical mixtures (Larsen et al. 1992). In addition, these mixtures also contain a number of contaminants in parts per million levels, such as PCDFs, polychlorinated quaterphenyls (PCQs) and poly-chlorinated naphthalenes (PCNs) (de Voogt and Brinkman 1989). The commercial PCB products, such as the Aroclors, typically consist of 50 to 70 congeners. Most of these mixtures are liquids at room temperature. The physico-chemical properties of the commercial mixtures depend on the congener composition, but generally they are resistant to acids and bases, resistant to oxidation and hydrolysis, thermally stable, excellent electrical insulators, sparingly soluble in water and have low flammability (de Voogt and Brinkman 1989). These characteristics made them very useful in diverse industrial applications, such as liquid components of transformers, capacitors, heat-exchangers, and vacuum pumps. PCB mixtures have also been used in open systems, such as plasticizers, deinking solvents, water- proofing agents, sealing liquids, fire retardants and pesticides (de Voogt and Brinkman 1989). 2 Introduction 3.2 Physico-chemical properties of individual PCBs In 1980, Ballschmiter and Zell presented a numbering system for the 209 individual PCBs that follows the IUPAC rules (see Figure 1 and Table 1). Three years later, minor amendments to this system were suggested by Schulte and Malisch (1983). The molecular weights of the PCBs range from 188.7 to 498.7 based on the natural abundance of carbon, hydrogen, and chlorine (de Voogt and Brinkman 1989). The PCBs are soluble in organic solvents, oils and fats, but show an extremely low solubility in water, especially the more highly chlorinated biphenyls. In the literature, specific physico-chemical properties of individual PCBs may vary between measurements. These values are critical for modelling aspects such as the transport and fate, persistence, bioconcentration, and biological activity of the congeners. An important physico-chemical characteristic of the PCBs is their ability to rotate around the phenyl-phenyl bond. The conformation of the PCBs has been shown to be correlated with their toxicity, strength of adsorption to surfaces, and partition between various media. Although the non-ortho PCBs are often described as “the coplanar congeners”, all PCBs regardless of substitution pattern, are twisted (McKinney and Singh 1981). The energy barrier of rotation increases as the number of chlorine atoms in ortho positions increases. The electron diffraction technique has been used to estimate the dihedral angles of some PCBs. For instance, Almenningen et al. (1985) reported this angle to be 44° for the non-ortho PCB 2 and Bastiansen (1950) reported 74° for the di-ortho PCB 4. The energy barrier of internal rotation for the tri- and tetra-ortho PCBs severely restricts their rotation (Kaiser 1974). Among the 209 PCBs, 19 are predicted to be atropisomers, i.e. they are conformationally stable and optically active under most environmental conditions (Kaiser 1974). The atropisomers can be isolated by liquid chromatography with chiral stationary phases (Haglund 1996). Further, the biological potency, both in vitro and in vivo, has been shown to differ between enantiomers of the same atropisomeric PCB (Püttmann et al. 1989). 3