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In silico tools in risk assessment: of industrial chemicals in general and non-dioxin-like PCBs in particular
Umeå University, Faculty of Science and Technology, Department of Chemistry.
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Industrial chemicals in European Union produced or imported in volumes above 1 tonne annually, necessitate a registration within REACH. A common problem, concerning these chemicals, is deficient information and lack of data for assessing the hazards posed to human health and the environment. Animal studies for the type of toxicological information needed are both expensive and time consuming, and to that an ethical aspect is added. Alternative methods to animal testing are thereby requested. REACH have called for an increased use of

in silico tools for non-testing data as structure-activity relationships (SARs), quantitative structure-activity relationships (QSARs), and read-across. The main objective of the studies underlying this thesis is related to explore and refine the use of in silico tools in a risk assessment context of industrial chemicals. In particular, try to relate properties of the molecular structure to the toxic effect of the chemical substance, by using principles and methods of computational chemistry. The initial study was a survey of all industrial chemicals; the Industrial chemical map was created. A part of this map was identified including chemicals of potential concern. Secondly, the environmental pollutants, polychlorinated biphenyls (PCBs) were examined and in particular the non-dioxin-like PCBs (NDL-PCBs). A set of 20 NDL-PCBs was selected to represent the 178 PCB congeners with three to seven chlorine substituents. The selection procedure was a combined process including statistical molecular design for a representative selection and expert judgements to be able to include congeners of specific interest. The 20 selected congeners were tested in vitro in as much as 17 different assays. The data from the screening process was turned into interpretable toxicity profiles with multivariate methods, used for investigation of potential classes of NDL-PCBs. It was shown that NDL-PCBs cannot be treated as one group of substances with similar mechanisms of action. Two groups of congeners were identified. A group including in general lower chlorinated congeners with a higher degree of ortho substitution showed a higher potency in more assays (including all neurotoxic assays). A second group included abundant congeners with a similar toxic profile that might contribute to a common toxic burden. To investigate the structure-activity pattern of PCBs effect on DAT in rat striatal synaptosomes, ten additional congeners were selected and tested in vitro. NDL-PCBs were shown to be potent inhibitors of DAT binding. The congeners with highest DAT inhibiting potency were tetra- and penta-chlorinated with 2-3 chlorine atoms in ortho-position. The model was not able to distinguish the congeners with activities in the lower μM range, which could be explained by a relatively unspecific response for the lower ortho chlorinated PCBs.

Abstract [sv]

Den europeiska kemikalielagstiftningen REACH har fastställt att kemikalier som produceras eller importeras i en mängd över 1 ton per år, måste registreras och riskbedömmas. En uppskattad siffra är att detta gäller för 30 000 kemikalier. Problemet är dock att data och information ofta är otillräcklig för en riskbedömning. Till stor del har djurförsök använts för effektdata, men djurförsök är både kostsamt och tidskrävande, dessutom kommer den etiska aspekten in. REACH har därför efterfrågat en undersökning av möjligheten att använda in silico verktyg för att bidra med efterfrågad data och information. In silico har en ungefärlig betydelse av i datorn, och innebär beräkningsmodeller och metoder som används för att få information om kemikaliers egenskaper och toxicitet. Avhandlingens syfte är att utforska möjligheten och förfina användningen av in silico verktyg för att skapa information för riskbedömning av industrikemikalier. Avhandlingen beskriver kvantitativa modeller framtagna med kemometriska metoder för att prediktera, dvs förutsäga specifika kemikaliers toxiska effekt.

I den första studien (I) undersöktes 56 072 organiska industrikemikalier. Med multivariata metoder skapades en karta över industrikemikalierna som beskrev dess kemiska och fysikaliska egenskaper. Kartan användes för jämförelser med kända och potentiella miljöfarliga kemikalier. De mest kända miljöföroreningarna visade sig ha liknande principal egenskaper och grupperade i kartan. Genom att specialstudera den delen av kartan skulle man kunna identifiera fler potentiellt farliga kemiska substanser. I studie två till fyra (II-IV) specialstuderades miljögiftet PCB. Tjugo PCBs valdes ut så att de strukturellt och fysiokemiskt representerade de 178 PCB kongenerna med tre till sju klorsubstituenter. Den toxikologiska effekten hos dessa 20 PCBs undersöktes i 17 olika in vitro assays. De toxikologiska profilerna för de 20 testade kongenerna fastställdes, dvs vilka som har liknande skadliga effekter och vilka som skiljer sig åt. De toxicologiska profilerna användes för klassificering av PCBs. Kvantitativa modeller utvecklades för prediktioner, dvs att förutbestämma effekter hos ännu icke testade PCBs, och för att få ytterligare kunskap om strukturella egenskaper som ger icke önskvärda effekter i människa och natur. Information som kan användas vid en framtida riskbedömning av icke-dioxinlika PCBs. Den sista studien (IV) är en struktur-aktivitets studie som undersöker de icke-dioxinlika PCBernas hämmande effekt av signalsubstansen dopamin i hjärnan.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet , 2012. , 62 p.
Keyword [en]
Chemometrics, industrial chemicals, in silico tools, molecular descriptors, non-dioxin-like PCBs, partial least-squares (PLS), principal component analysis (PCA), quantitative structure-activity relationship (QSAR), REACH, risk assessment (RA), statistical molecular design, structure-activity relationship (SAR)
National Category
Other Chemistry Topics
Identifiers
URN: urn:nbn:se:umu:diva-50609ISBN: 978-91-7459-342-6 (print)OAI: oai:DiVA.org:umu-50609DiVA: diva2:465850
Public defence
2012-01-16, KBC-huset, KB3B1, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2011-12-23 Created: 2011-12-15 Last updated: 2011-12-15Bibliographically approved
List of papers
1. A multivariate chemical map of industrial chemicals: Assessment of various protocols for identification of chemicals of potential concern
Open this publication in new window or tab >>A multivariate chemical map of industrial chemicals: Assessment of various protocols for identification of chemicals of potential concern
2009 (English)In: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 76, no 7, 878-884 p.Article in journal (Refereed) Published
Abstract [en]

In present study the Industrial chemical map was created, and investigated. Molecular descriptors were calculated for 56 072 organic substances from the European inventory of existing commercial chemical substances (EINECS). The resulting multivariate dataset was subjected to principal component analysis (PCA), giving five principal components, mainly reflecting size, hydrophobicity, flexibility, halogenation and electronical properties. It is these five PCs that form the basis of the map of organic, industrial chemicals, the Industrial chemical map. The similarities and diversity in chemical characteristics of the substances in relation to their persistence (P), bioaccumulation (B) and long-range transport potential were then examined, by superimposing five sets of entries obtained from other relevant databases onto the Industrial chemical map. These sets displayed very similar diversity patterns in the map, although with a spread in all five PC vectors. Substances listed by the United Nations Environment Program as persistent organic pollutants (UNEP POPs) were on the other hand clearly grouped with respect to each of the five PCs. Illustrating similarities and differences in chemical properties are one of the strengths of the multivariate data analysis method, and to be able to make predictions of, and investigate new chemicals. Further, the results demonstrate that non-testing methods as read-across, based on molecular similarities, can reduce the requirements to test industrial chemicals, provided that they are applied carefully, in combination with sound chemical knowledge.

Place, publisher, year, edition, pages
Elsevier, 2009
Keyword
Hazard identification, Persistent organic pollutants, Risk assessment, Molecular similarities, Non-testing methods, Read-across
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-23516 (URN)10.1016/j.chemosphere.2009.05.011 (DOI)
Note
Accepted 13 May 2009. Available online 9 June 2009. Available from: 2009-06-23 Created: 2009-06-23 Last updated: 2011-12-15Bibliographically approved
2. Selection of non-dioxin-like PCBs for in vitro testing on the basis of environmental abundance and molecular structure
Open this publication in new window or tab >>Selection of non-dioxin-like PCBs for in vitro testing on the basis of environmental abundance and molecular structure
2008 (English)In: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 71, no 10, 1909-1915 p.Article in journal (Refereed) Published
Abstract [en]

The non-dioxin-like polychlorinated biphenyls (NDL-PCBs) constitute the major proportion of PCBs found in food and human tissues. It is important to improve our understanding of the toxicity, environmental and human risks associated with the NDL-PCBs, since their toxicology is incompletely characterized and a human health risk assessment is required. This paper discusses the selection of a training set of 20 tri- to hepta-chlorinated biphenyls, PCBs 19, 28, 47, 51, 52, 53, 74, 95, 100, 101, 104, 118, 122, 128, 136, 138, 153, 170, 180, and 190. Suggested for comprehensive screening using in vitro assays to identify critical mechanisms of toxicological action. The selected PCBs form a balanced basis for developing of quantitative structure-activity relationship (QSAR) models for prediction of physicochemical and toxicological properties of non-tested PCB congeners. Chemical and physical properties, environmental abundance and toxicological activities of the congeners were considered during the selection process. A complementary set of PCBs, a reference set, was selected using D-optimal onion design including PCBs 18, 20, 28, 30, 37, 40, 50, 54, 60, 77, 82, 99, 122, 132, 153, 161, 170, 188, 192, and 193. Congeners of this set are well suited for validation of QSAR models developed using the training set. For visualization of the chemical diversity of environmentally abundant PCBs and congeners of the training and reference sets, principal component analysis (PCA) was used. Statistical molecular design was used to verify the structural representation. As a reference structure for dioxin-like PCBs, PCB 126 was added in the training set. The selected set of NDL-PCBs is proposed for use in toxicological testing programs to provide rational basis for risk assessment of the NDL-PCBs.

Place, publisher, year, edition, pages
Elsevier, 2008
Keyword
NDL-PCBs, Multivariate data analysis, Experimental design, Training set, Validation
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-9641 (URN)10.1016/j.chemosphere.2008.01.007 (DOI)
Available from: 2008-05-07 Created: 2008-05-07 Last updated: 2011-12-15Bibliographically approved
3. Multivariate toxicity profiles and QSAR modeling of non-dioxin-like PCBs: an investigation of in vitro screening data from ultra-pure congeners
Open this publication in new window or tab >>Multivariate toxicity profiles and QSAR modeling of non-dioxin-like PCBs: an investigation of in vitro screening data from ultra-pure congeners
Show others...
2011 (English)In: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 85, no 9, 1423-1429 p.Article in journal (Refereed) Published
Abstract [en]

The non-dioxin-like PCBs (NDL-PCBs) found in food and human samples have a complex spectrum of adverse effects, but lack a detailed risk assessment. The toxicity profiles of 21 carefully selected PCBs (19 NDL-PCBs) were identified by in vitro screening in 17 different assays on specific endpoints related to neurotoxicity, endocrine disruption and tumor promotion. To ensure that the test results were not affected by polychlorinated dioxins, dibenzofurans or DL-PCB contaminants, the NDL-PCB congeners were thoroughly purified before testing. Principal component analysis (PCA) was used to derive general toxicity profiles from the in vitro screening data. The toxicity profiles indicated different structure-activity relationships (SAR) and distinct mechanisms of action. The analysis also indicated that the NDL-PCBs could be divided into two groups. The first group included generally smaller, ortho-substituted congeners, comprising PCB 28, 47, 51, 52, 53, 95, 100, 101, 104 and 136, with PCB 95, 101 and 136 as generally being most active. The second group comprising PCB 19, 74, 118, 122, 128, 138, 153, 170, 180 and 190 had lower biological activity in many of the assays, except for three endocrine-related assays. The most abundant congeners, PCB 138, 153, 170, 180 and 190, cluster in the second group, and thereby show similar SAR. Two quantitative structure-activity relationship (QSAR) models could be developed that added information to the SAR and could aid in risk assessments of NDL-PCBs. The QSAR models predicted a number of congeners as active and among these e.g., PCB 18, 25, 45 and 49 have been found in food or human samples.

Place, publisher, year, edition, pages
Elsevier, 2011
Keyword
non-dioxin-like PCBs, ultra-pure, in vitro screening, toxicity profiles, principal component analysis, QSAR
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-46977 (URN)10.1016/j.chemosphere.2011.08.019 (DOI)21890175 (PubMedID)
Available from: 2011-09-19 Created: 2011-09-19 Last updated: 2017-12-08Bibliographically approved
4. Non-dioxin-like PCBs inhibit [3H]WIN-35,428 binding to dopamine active transporter:  a structure activity relationship study
Open this publication in new window or tab >>Non-dioxin-like PCBs inhibit [3H]WIN-35,428 binding to dopamine active transporter:  a structure activity relationship study
Show others...
2013 (English)In: Naunyn-Schmiedeberg's Archives of Pharmacology, ISSN 0028-1298, E-ISSN 1432-1912Article in journal (Other academic) Submitted
National Category
Other Chemistry Topics
Research subject
Toxicology
Identifiers
urn:nbn:se:umu:diva-50610 (URN)
Available from: 2011-12-15 Created: 2011-12-15 Last updated: 2017-12-08Bibliographically approved

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