| 1. |
- Ghorbanzadeh, Mehdi, et al.
(författare)
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Binary classification model to predict developmental toxicity of industrial chemicals in zebrafish
- 2016
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Ingår i: Journal of Chemometrics. - : Wiley-Blackwell. - 0886-9383 .- 1099-128X. ; 30:6, s. 298-307
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Tidskriftsartikel (refereegranskat)abstract
- The identification of industrial chemicals, which may cause developmental effects, is of great importance for an early detection of hazardous chemicals. Accordingly, categorical quantitative structure-activity relationship (QSAR) models were developed, based on developmental toxicity profile data for zebrafish from the ToxCast Phase I testing, to predict the toxicity of a large set of high and low production volume chemicals (H/LPVCs). QSARs were created using linear (LDA), quadratic, and partial least squares-discriminant analysis with different chemical descriptors. The predictions of the best model (LDA) were compared with those obtained by the freely available QSAR model VEGA, created based on a dataset with a different chemical domain. The results showed that despite similar accuracy (AC) of both models, the LDA model is more specific than VEGA and shows a better agreement between sensitivity (SE) and specificity (SP). Applying a 90% confidence level on the Lou model led to even better predictions showing SE of 0.92, AC of 0.95, and geometric mean of SE and SP (G) of 0.96 for the prediction set. The LDA model predicted 608 H/LPVCs as toxicants among which 123 chemicals fall inside the AD of the VEGA model, which predicted 112 of those as toxicants. Among the 112 chemicals predicted as toxic H/LPVCs, 23 have been previously reported as developmental toxicants. The here presented LDA model could be used to identify and prioritize H/LPVCs for subsequent developmental toxicity assessment, as a screening tool of potential developmental effects of new chemicals, and to guide synthesis of safer alternative chemicals.
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| 2. |
- Ghorbanzadeh, Mehdi, et al.
(författare)
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In vitro and in silico derived relative effect potencies of Ah-Receptor-mediated effects by PCDD/Fs and PCBs in rat, mouse, and guinea pig CALUX Cell Lines
- 2014
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Ingår i: Chemical Research in Toxicology. - : American Chemical Society (ACS). - 0893-228X .- 1520-5010. ; 27:7, s. 1120-1132
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Tidskriftsartikel (refereegranskat)abstract
- For a better understanding of species-specific relative effect potencies (REPs), responses of dioxin-like compounds (DLCs) were assessed. REPs were calculated using chemical-activated luciferase gene expression assays (CALUX) derived from guinea pig, rat, and mouse cell lines. Almost all 20 congeners tested in the rodent cell lines were partial agonists and less efficacious than 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). For this reason, REPs were calculated for each congener using concentrations at which 20% of the maximal TCDD response was reached,(REP20TCDD). REP20TCDD values obtained for PCDD/Fs were comparable with their toxic equivalency factors assigned by the World Health Organization (WHO-TEF), while those for PCBs were in general lower than the WHO-TEF values. Moreover, the guinea pig cell line was the most sensitive as indicated by the 20% effect concentrations of TCDD of 1.5, 5.6, and 11.0 pM for guinea pig, rat, and mouse cells, respectively. A similar response pattern was observed using multivariate statistical analysis between the three CALLTX assays and the WHO-TEFs. The mouse assay showed minor deviation due to higher relative induction potential for 2,3,7,8-tetrachlorodibenzofuran and 2,3,4,6,7,8-hexachlorodibenzofuran and lower for 1,2,3,4,6,7,8-heptachlorodibenzofuran and 3,3',4,4',5-pentachlorobiphenyl (PCB126). 2,3,7,8-Tetrachlorodibenzofuran was more than two times more potent in the mouse assay as compared with that of rat and guinea pig cells, while measured REP20TCDD for PCB126 was lower in mouse cells (0.05) as compared with that of the guinea pig (0.2) and rat (0.07). In order to provide REP20TCDD values for all WHO-TEF assigned compounds, quantitative structure activity relationship (QSAR) models were developed. The QSAR models showed that specific electronic properties and molecular surface characteristics play important roles in the AhR-mediated response. In silica derived REP20TCDD values were generally consistent with the WHO-TEFs with a few exceptions. The QSAR models indicated that, e.g., 1,2,3,7,8-pentachlorodibenzofuran and 1,2,3,7,8,9-hexachlorodibenzofuran were more potent than given by their assigned WHO-TEF values, and the non-ortho PCB 81 was predicted, based on the guinea-pig model, to be 1 order of magnitude above its WHO-TEF value. By combining in vitro and in silico approaches, REPs were established for all WHO-TEF assigned compounds (except OCDD), which will provide future guidance in testing AhR-mediated responses of DLCs and to increase our understanding of species variation in AhR-mediated effects.
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| 4. |
- Zhang, Jin, et al.
(författare)
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In Silico Approach To Identify Potential Thyroid Hormone Disruptors among Currently Known Dust Contaminants and Their Metabolites
- 2015
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Ingår i: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 49:16, s. 10099-10107
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Tidskriftsartikel (refereegranskat)abstract
- Thyroid hormone disrupting chemicals (THDCs) interfere with the thyroid hormone system and may induce multiple severe physiological disorders. Indoor dust ingestion is a major route of THDCs exposure in humans, and one of the molecular targets of these chemicals is the hormone transporter transthyretin (TTR). To virtually screen indoor dust contaminants and their metabolites for THDCs targeting TTR, we developed a quantitative structure activity relationship (QSAR) classification model. The QSAR model was applied to an in-house database including 485 organic dust contaminants reported from literature data and their 433 in silico derived metabolites. The model predicted 37 (7.6%) dust contaminants and 230 (53.1%) metabolites as potential TTR binders. Four new THDCs were identified after testing 23 selected parent dust contaminants in a radio-ligand TTR binding assay; 2,2',4,4'-tetrahydroxybenzophenone, perfluoroheptanesulfonic acid, 3,5,6-trichloro-2-pyridinol, and 2,4,5-trichlorophenoxyacetic acid. These chemicals competitively bind to TTR with 50% inhibition (IC50) values at or below 10 mu M. Molecular docking studies suggested that these THDCs interacted similarly with TTR via the residue Ser117A, but their binding poses were dissimilar to the endogenous ligand T4. This study identified new THDCs using an in silico approach in combination with bioassay testing and highlighted the importance of metabolic activation for TTR binding.
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