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On the use of electronic descriptors for QSAR modelling of PCDDs, PCDFs and dioxin-like PCBs£:
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
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2013 (English)In: SAR and QSAR in environmental research (Print), ISSN 1062-936X, E-ISSN 1029-046X, Vol. 24, no 6, 461-479 p.Article in journal (Refereed) Published
Abstract [en]

The electronic properties of 29 polychlorinated dibenzo-p-dioxins and dibenzofurans and dioxin-like polychlorinated biphenyls that have been included in the toxic equivalency factor system have been investigated and used to derive quantum mechanical (QM) chemical descriptors for QSAR modelling. Their utility in this context was investigated alongside descriptors based on ultraviolet absorption data and traditional 2D descriptors including log Kow, polarizability, molecular surface properties, van der Waals volume and selected connectivity indices. The QM descriptors were calculated using the semi-empirical AM1 method and the density functional theory method B3-LYP/6-31G(∗∗). Atom-specific and molecular quantum chemical descriptors were calculated to compare the electronic properties of dioxin-like compounds regardless of their chemical class, with particular emphasis on the lateral positions. Multivariate analysis revealed differences between the chemical classes in terms of their electronic properties and also highlighted differences between congeners. The results obtained demonstrated the importance of considering molecular orbital energies, but also indicated that the ratios of the coefficients of the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) at the lateral carbons were important. In addition, the digitalized UV spectra contained chemical information that provided crucial insights into dioxin-like activity.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2013. Vol. 24, no 6, 461-479 p.
Keyword [en]
Dioxins, ultraviolet, electronic descriptors, density functional theory, semi-empirical, QSAR, toxic equivalency factor
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:umu:diva-71652DOI: 10.1080/1062936X.2013.791719ISI: 000320184100003PubMedID: 23724952OAI: oai:DiVA.org:umu-71652DiVA: diva2:625213
Note

Special issue: 15th International Workshop on Quantitative Structure-Activity Relationships in Environmental and Health Sciences (QSAR2012). 

Available from: 2013-06-04 Created: 2013-06-04 Last updated: 2017-09-14Bibliographically approved
In thesis
1. Computational methods for analyzing dioxin-like compounds and identifying potential aryl hydrocarbon receptor ligands: multivariate studies based on human and rodent in vitro data
Open this publication in new window or tab >>Computational methods for analyzing dioxin-like compounds and identifying potential aryl hydrocarbon receptor ligands: multivariate studies based on human and rodent in vitro data
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) are omnipresent and persistent environmental pollutants. In particular, 29 congeners are of special concern, and these are usually referred to as dioxin-like compounds (DLCs). In the European Union, the risks associated with DLCs in food products are estimated by a weighted sum of the DLCs’ concentrations. These weights, also called toxic equivalency factors (TEFs), compare the DLCs’ potencies to the most toxic congener, 2,3,7,8-tetrachloro-dibenzo-p-dioxin (2378- TCDD). The toxicological effects of PCDD/Fs and PCBs are diverse, ranging from chloracne and immunological effects in humans to severe weight loss, thymic atrophy, hepatotoxicity, immunotoxicity, endocrine disruption, and carcinogenesis in rodents.

Here, the molecular structures of DLCs were used as the basis to study the congeneric differences in in vitro data from both human and rodent cell responses related to the aryl hydrocarbon receptor (AhR). Based on molecular orbital densities and partial charges, we developed new ways to describe DLCs, which proved to be useful in quantitative structure-activity relationship modeling. This thesis also provides a new approach, the calculation of the consensus toxicity factor (CTF), to condense information from a battery of screening tests. The current TEFs used to estimate the risk of DLCs in food are primarily based on in vivo information from rat and mouse experiments. Our CTFs, based on human cell responses, show clear differences compared to the current TEFs. For instance, the CTF of 23478-PeCDF is as high as the CTF for 2378-TCDD, and the CTF of PCB 126 is 30 times lower than the corresponding TEF. Both of these DLCs are common congeners in fish in the Baltic Sea. Due to the severe effects of DLCs and their impact on environmental and human health, it is crucial to determine if other compounds have similar effects. To find such compounds, we developed a virtual screening protocol and applied it to a set of 6,445 industrial chemicals. This protocol included a presumed 3D representation of AhR and the structural and chemical properties of known AhR ligands. This screening resulted in a priority list of 28 chemicals that we identified as potential AhR ligands.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2017. 66 p.
Keyword
dioxin-like compounds, multivariate analysis, toxic equivalency factor, quantitative structure-activity relationship, descriptors, virtual screening, in vitro, species variation, aryl hydrocarbon receptor
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-139487 (URN)978-91-7601-736-4 (ISBN)
Public defence
2017-10-19, KB.E3.01 (Lilla Hörsalen), KBC-huset, Umeå, 13:00 (English)
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Available from: 2017-09-28 Created: 2017-09-14 Last updated: 2017-10-02Bibliographically approved

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Larsson, MalinKumar Mishra, BrijeshTysklind, MatsLinusson, AnnaAndersson, Patrik L.
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