Elucidating the Aryl Hydrocarbon Receptor Antagonism from a Chemical-Structural Perspective

[en] The aryl hydrocarbon receptor (AhR) plays an important role in several biological processes such as reproduction, immunity and homoeostasis. However, little is known on the chemical-structural and physicochemical features that influence the activity of AhR antagonistic modulators. In the present report, in vitro AhR antagonistic activity evaluations, based on a chemical-activated luciferase gene expression (AhR-CALUX) bioassay, and an extensive literature review were performed with the aim of constructing a structurally diverse database of contaminants and potentially toxic chemicals. Subsequently, QSAR models based on Linear Discriminant Analysis and Logistic Regression, as well as two toxicophoric hypotheses were proposed to model the AhR antagonistic activity of the built dataset. The QSAR models were rigorously validated yielding satisfactory performance for all classification parameters. Likewise, the toxicophoric hypotheses were validated using a diverse set of 350 decoys, demonstrating adequate robustness and predictive power. Chemical interpretations of both the QSAR and toxicophoric models suggested that hydrophobic constraints, the presence of aromatic rings and electron-acceptor moieties are critical for the AhR antagonism. Therefore, it is hoped that the deductions obtained in the present study will contribute to elucidate further on the structural and physicochemical factors influencing the AhR antagonistic activity of chemical compounds.

Research Center/Unit :

CART - Centre Interfacultaire d'Analyse des Résidus en Traces - ULiège

Disciplines :

Biochemistry, biophysics & molecular biology

Author, co-author :

Goya-Jorge, Elizabeth

Doan Thi Que ; Université de Liège - ULiège > Form. doct. sc. (bioch., biol. mol. cel., bioinf. - paysage)

Scippo, Marie-Louise ; Université de Liège - ULiège > Département de sciences des denrées alimentaires (DDA) > Analyse des denrées alimentaires

Muller, Marc ; Université de Liège - ULiège > Département des sciences de la vie > I3-Laboratory for Organogenesis and Regeneration

Giner, Rosa

Barigye, Sephen

Gozalbes, Rafael

Language :

English

Title :

Elucidating the Aryl Hydrocarbon Receptor Antagonism from a Chemical-Structural Perspective

Publication date :

09 January 2020

Journal title :

SAR and QSAR in Environmental Research

ISSN :

1062-936X

eISSN :

1029-046X

Publisher :

Taylor & Francis, United Kingdom

Volume :

Issue :

Pages :

209-226

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.tandfonline.com/eprint/7J83XDZVPIKUYQERRJQA/full?target=10.1080/1062936X.2019.1708460

European Projects :

H2020 - 722634 - PROTECTED - PROTECTion against Endocrine Disruptors; Detection, mixtures, health effects, risk assessment and communication.

Name of the research project :

PROTECTED

Funders :

EC - European Commission
EU - European Union

Funding number :

722634

Funding text :

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 722634.

Data Set :

Supplementary material

Available on ORBi :

since 10 February 2020

Statistics

Number of views

152 (14 by ULiège)

Number of downloads

309 (5 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

OpenAlex citations

Bibliography

D.W., Nebert, Aryl hydrocarbon receptor (AHR): “Pioneer member” of the basic-helix/loop/helix per-Arnt-sim (bHLH/PAS) family of “sensors” of foreign and endogenous signals, Prog. Lipid Res. 67 (2017), pp. 38–57. doi:10.1016/j.plipres.2017.06.001.
K., Kawajiri and Y., Fuji-Kuriyama, The aryl hydrocarbon receptor: A multifunctional chemical sensor for host defense and homeostatic maintenance, Exp. Anim. 66 (2016), pp. 75–89. doi:10.1538/expanim.16-0092.
K.W., Bock, From TCDD-mediated toxicity to searches of physiologic AHR functions, Biochem. Pharmacol. 155 (2018), pp. 419–424. doi:10.1016/j.bcp.2018.07.032.
R., Pohjanvirta, The AH Receptor in Biology and Toxicology, John Wiley and Sons, Hoboken, NJ, 2011.
L., Bonati, D., Corrada, S., Giani Tagliabue, and S., Motta, Molecular modeling of the AhR structure and interactions can shed light on ligand-dependent activation and transformation mechanisms, Curr. Opin. Toxicol. 2 (2017), pp. 42–49. doi:10.1016/j.cotox.2017.01.011.
T., Hamers, J.H., Kamstra, P.H., Cenijn, K., Pencikova, L., Palkova, P., Simeckova, J., Vondracek, P.L., Andersson, M., Stenberg, and M., Machala, In vitro toxicity profiling of ultrapure non-dioxin-like polychlorinated biphenyl congeners and their relative toxic contribution to PCB mixtures in humans, Toxicol. Sci. 121 (2011), pp. 88–100. doi:10.1093/toxsci/kfr043.
P., Brenerová, T., Hamers, J.H., Kamstra, J., Vondráček, S., Strapáčová, P.L., Andersson, and M., Machala, Pure non-dioxin-like PCB congeners suppress induction of AhR-dependent endpoints in rat liver cells, Environ. Sci. Pollut. Res. 23 (2016), pp. 2099–2107. doi:10.1007/s11356-015-4819-6.
L., Stejskalova, Z., Dvorak, and P., Pavek, Endogenous and exogenous ligands of aryl hydrocarbon receptor: Current state of art, Curr. Drug Metab. 12 (2011), pp. 198–212. doi:10.2174/138920011795016818.
G.A., Reed, K.S., Peterson, H.J., Smith, J.C., Gray, D.K., Sullivan, M.S., Mayo, J.A., Crowell, and A., Hurwitz, A phase I study of indole-3-carbinol in women: Tolerability and effects, Cancer Epidemiol. Biomarkers Prev. 14 (2005), pp. 1953–1960. doi:10.1158/1055-9965.EPI-05-0121.
O., Hankinson, The role of AHR-inducible cytochrome P450s in metabolism of polyunsaturated fatty acids, Drug Metab. Rev. 48 (2016), pp. 342–350. doi:10.1080/03602532.2016.1197240.
A., Puga, Y., Xia, and C., Elferink, Role of the aryl hydrocarbon receptor in cell cycle regulation, Chem. Biol. Interact. 141 (2002), pp. 117–130. doi:10.1016/S0009-2797(02)00069-8.
C., Esser, A., Rannug, and B., Stockinger, The aryl hydrocarbon receptor in immunity, Trends Immunol. 30 (2009), pp. 447–454. doi:10.1016/j.it.2009.06.005.
C., Duval, E., Blanc, and X., Coumoul, Aryl hydrocarbon receptor and liver fibrosis, Curr. Opin. Toxicol. 8 (2018), pp. 8–13. doi:10.1016/j.cotox.2017.11.010.
K., Pěnčíková, L., Svržková, S., Strapáčová, J., Neča, I., Bartoňková, Z., Dvořák, M., Hýžďalová, J., Pivnička, L., Pálková, H.J., Lehmler, X., Li, J., Vondráček, and M., Machala, In vitro profiling of toxic effects of prominent environmental lower-chlorinated PCB congeners linked with endocrine disruption and tumor promotion, Environ. Pollut. 237 (2018), pp. 473–486. doi:10.1016/j.envpol.2018.02.067.
S., Safe, S.O., Lee, and U.H., Jin, Role of the aryl hydrocarbon receptor in carcinogenesis and potential as a drug target, Toxicol. Sci. 135 (2013), pp. 1–16. doi:10.1093/toxsci/kft128.
Z., Xue, D., Li, W., Yu, Q., Zhang, X., Hou, Y., He, and X., Kou, Mechanisms and therapeutic prospects of polyphenols as modulators of the aryl hydrocarbon receptor, Food Funct. 8 (2017), pp. 1414–1437. doi:10.1039/C6FO01810F.
R., Nakai, S., Fukuda, M., Kawase, Y., Yamashita, and H., Ashida, Curcumin and its derivatives inhibit 2,3,7,8,-tetrachloro-dibenzo-p-dioxin-induced expression of drug metabolizing enzymes through aryl hydrocarbon receptor-mediated pathway, Biosci. Biotechnol. Biochem. 82 (2017), pp. 616–628. doi:10.1080/09168451.2017.1386086.
H., Kandárová and S., Letaáiová, Alternative methods in toxicology: Pre-validated and validated methods, Interdiscip. Toxicol. 4 (2011), pp. 107–113. doi:10.2478/v10102-011-0018-6.
A., Cherkasov, E.N., Muratov, D., Fourches, A., Varnek, I.I., Baskin, M., Cronin, J., Dearden, P., Gramatica, Y.C., Martin, R., Todeschini, V., Consonni, V.E., Kuz’min, R., Cramer, R., Benigni, C., Yang, J., Rathman, L., Terfloth, J., Gasteiger, A., Richard, and A., Tropsha, QSAR modeling: Where have you been? Where are you going to? J. Med. Chem. 57 (2014), pp. 4977–5010. doi:10.1021/jm4004285.
L.G., Valerio, C., Yang, K.B., Arvidson, and N.L., Kruhlak, A structural feature-based computational approach for toxicology predictions, Expert Opin. Drug Metab. Toxicol. 6 (2010), pp. 505–518. doi:10.1517/17425250903499286.
D., Szöllösi, Á., Erdei, G., Gyimesi, C., Magyar, and T., Hegedüs, Access path to the ligand binding pocket may play a role in xenobiotics selection by AhR, PLoS ONE 11 (2016), pp. 1–22. doi:10.1371/journal.pone.0146066.
A.D., Şahin and M.T., Saçan, Understanding the toxic potencies of xenobiotics inducing TCDD/TCDF-like effects, SAR QSAR Environ. Res. 29 (2018), pp. 117–131. doi:10.1080/1062936X.2017.1414075.
M.K., Gadhwal, S., Patil, P., D’mello, and A., Joshi, Homology modeling of aryl hydrocarbon receptor and docking of agonists and antagonists, Int. J. Pharm. Pharm. Sci. 5 (2013), pp. 76–81.
D., Dolciami, M., Gargaro, B., Cerra, G., Scalisi, L., Bagnoli, G., Servillo, M.A.D., Fazia, P., Puccetti, F.J., Quintana, F., Fallarino, and A., Macchiarulo, Binding mode and structure–activity relationships of ITE as an aryl hydrocarbon receptor (AhR) agonist, ChemMedChem 13 (2018), pp. 270–279. doi:10.1002/cmdc.201700669.
S.-H., Seok, W., Lee, L., Jiang, K., Molugu, A., Zheng, Y., Li, S., Park, C.A., Bradfield, and Y., Xing, Structural hierarchy controlling dimerization and target DNA recognition in the AHR transcriptional complex, Proc. Natl. Acad. Sci. 114 (2017), pp. 5431–5436. doi:10.1073/pnas.1617035114.
G., Suzuki, M., Nakamura, C., Michinaka, N.M., Tue, H., Handa, and H., Takigami, Dioxin-like activity of brominated dioxins as individual compounds or mixtures in in vitro reporter gene assays with rat and mouse hepatoma cell lines, Toxicol. Vitro 44 (2017), pp. 134–141. doi:10.1016/j.tiv.2017.06.025.
S., Sciuto, M., Prearo, R., Desiato, C., Bulfon, E.A.V., Burioli, G., Esposito, C., Guglielmetti, L., Dell’atti, G., Ru, D., Volpatti, P.L., Acutis, and F., Martucci, Dioxin-like compounds in lake fish species: Evaluation by DR-CALUX bioassay, J. Food Prot. 81 (2018), pp. 842–847. doi:10.4315/0362-028X.JFP-17-476.
A.L.J., Nuerla, X.L., Qiao, J., Li, D.M., Zhao, X.H., Yang, Q., Xie, and J.W., Chen, Effects of substituent position on the interactions between PBDEs/PCBs and DOM, Chin. Sci. Bull. 58 (2013), pp. 884–889. doi:10.1007/s11434-012-5464-9.
R., Panda, A.S.S., Cleave, and P., Suresh, In silico predictive studies of mAHR congener binding using homology modelling and molecular docking, Toxicol. Ind. Health 30 (2014), pp. 765–776. doi:10.1177/0748233712463774.
H.F., Berntsen, V., Berg, C., Thomsen, E., Ropstad, and K.E., Zimmer, The design of an environmentally relevant mixture of persistent organic pollutants for use in in vivo and in vitro studies, J. Toxicol. Environ. Health Part A 24 (2017), pp. 1002–1016. doi:10.1080/15287394.2017.1354439.
A.J., Murk, J., Legler, M.S., Denison, J.P., Giesy, C., Van de Guchte, and A., Brouwer, Chemical-activated luciferase gene expression (CALUX): A novel in vitro bioassay for Ah receptor active compounds in sediments and pore water, Fundam. Appl. Toxicol. 33 (1996), pp. 149–160. doi:10.1006/faat.1996.0152.
OECD, Test No. 455: Performance-Based Test Guideline for Stably Transfected Transactivation in Vitro Assays to Detect Estrogen Receptor Agonists and Antagonists, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, 2016.
R., Todeschini and V., Consonni, Molecular Descriptors for Chemoinformatics, WILEY-VCH, Weinheim, Germany, 2009.
C.W., Yap, PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints, J. Comput. Chem. 32 (2011), pp. 1466–1474. doi:10.1002/jcc.v32.7.
R.W.P., Urias, S.J., Barigye, Y., Marrero-Ponce, C.R., García-Jacas, J.R., Valdes-Martiní, and F., Perez-Gimenez, IMMAN: Free software for information theory-based chemometric analysis, Mol. Divers. 19 (2015), pp. 305–319. doi:10.1007/s11030-014-9565-z.
MATLAB MathWorks Inc R2017b 9.3.0.713579, MathWorks Inc, USA, 2017. software. Available at https://www.mathworks.com/.
STATISTICA StatSoft Inc v8.0. StatSoft Inc, USA, 2007. software. Available at http://www.statsoft.com.
J., Jaworska and N., Nikolova-Jeliazkova, How can structural similarity analysis help in category formation? SAR QSAR Environ. Res. 18 (2007), pp. 195–207. doi:10.1080/10629360701306050.
S., Kim, P.A., Thiessen, E.E., Bolton, J., Chen, G., Fu, A., Gindulyte, L., Han, J., He, S., He, B.A., Shoemaker, J., Wang, B., Yu, J., Zhang, and S.H., Bryant, PubChem substance and compound databases, Nucleic Acids Res. 44 (2016), pp. D1202–D1213. doi:10.1093/nar/gkv951.
S.L., Dixon, A.M., Smondyrev, and S.N., Rao, PHASE: A novel approach to pharmacophore modeling and 3D database searching, Chem. Biol. Drug Des. 67 (2006), pp. 370–372. doi:10.1111/j.1747-0285.2006.00384.x.
J.F., Truchon and C.I., Bayly, Evaluating virtual screening methods: Good and bad metrics for the “early recognition” problem, J. Chem. Inf. Model. 47 (2007), pp. 488–508. doi:10.1021/ci600426e.
M.M., Mysinger, M., Carchia, J.J., Irwin, and B.K., Shoichet, Directory of useful decoys, enhanced (DUD-E): Better ligands and decoys for better benchmarking, J. Med. Chem. 55 (2012), pp. 6582–6594. doi:10.1021/jm300687e.
T., Hamers, J.H., Kamstra, E., Sonneveld, A.J., Murk, M.H.A., Kester, P.L., Andersson, J., Legler, and A., Brouwer, In vitro profiling of the endocrine-disrupting potency of brominated flame retardants, Toxicol. Sci. 92 (2006), pp. 157–173. doi:10.1093/toxsci/kfj187.
C., Sammut and G., Webb (eds.), Encyclopedia of Machine Learning and Data Mining, 2nd ed., Vol. 32, Springer, New York, NY, 2018.
M., Ghorbanzadeh, K.I., Van Ede, M., Larsson, M.B.M., Van Duursen, L., Poellinger, S., Lücke-Johansson, M., Machala, K., Pěnčíková, J., Vondráček, M., van den Berg, M.S., Denison, T., Ringsted, and P.L., Andersson, 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, Chem. Res. Toxicol. 27 (2014), pp. 1120–1132. doi:10.1021/tx5001255.
OECD, Guidance Document on the Validation of (Quantitative) Structure-Activity Relationship [(Q)SAR] Models, 2014. OECD Series on Testing and Assessment OECD, No. 69, OECD Publishing, Paris.
O.F., Güner and J.P., Bowen, Setting the record straight: The origin of the pharmacophore concept, J. Chem. Inf. Model. 54 (2014), pp. 1269–1283. doi:10.1021/ci5000533.
D.P., Williams, Toxicophores: Investigations in drug safety, Toxicology 226 (2006), pp. 1–11. doi:10.1016/j.tox.2006.05.101.
P.K., Singh, A., Negi, P.K., Gupta, M., Chauhan, and R., Kumar, Toxicophore exploration as a screening technology for drug design and discovery: Techniques, scope and limitations, Arch. Toxicol. 90 (2016), pp. 1785–1802. doi:10.1007/s00204-015-1587-5.
L., Chen, D., Wu, H.P., Bian, G.L., Kuang, J., Jiang, W.H., Li, G.X., Liu, S., Zou, J., Huang, and Y., Tang, Selective ligands of estrogen receptor β discovered using pharmacophore mapping and structure-based virtual screening, Acta Pharmacol. Sin. 35 (2014), pp. 1333–1341. doi:10.1038/aps.2014.69.
S.S., Ashtekar, N.M., Bhatia, and M.S., Bhatia, Development of leads targeting ER-α in breast cancer: An in silico exploration from natural domain, Steroids 131 (2018), pp. 14–22. doi:10.1016/j.steroids.2017.12.016.
N., Lagarde, S., Delahaye, A., Jérémie, N., Ben Nasr, H., Guillemain, C., Empereur-Mot, V., Laville, T., Labib, M., Réau, F., Langenfeld, J.F., Zagury, and M., Montes, Discriminating agonist from antagonist ligands of the nuclear receptors using different chemoinformatics approaches, Mol. Inf. 36 (2017), pp. 1–16. doi:10.1002/minf.201700020.
R.T., Engeli, S.R., Rohrer, A., Vuorinen, S., Herdlinger, T., Kaserer, S., Leugger, D., Schuster, and A., Odermatt, Interference of paraben compounds with estrogen metabolism by inhibition of 17β-hydroxysteroid dehydrogenases, Int. J. Mol. Sci. 18 (2017). doi:10.3390/ijms18092007.
I.T., Jolliffe, Principal Component Analysis, 2nd ed., Vol. 98, Springer-Verlag, New York, NY, 2002.
K., Schomburg, H., Ehrlich, K., Stierand, and M., Rarey, From structure diagrams to visual chemical patterns, J. Chem. Inf. Model. 50 (2010), pp. 1529–1535. doi:10.1021/ci100209a.
L., Poellinger and D., Gullberg, Characterization of the hydrophobic properties of the receptor for 2,3,7,8-tetrachlorodibenzo-p-dioxin, Mol. Pharmacol. 27 (1985), pp. 271–276.
T., Tripathi and A.K., Saxena, 2D- QSAR studies on new stilbene derivatives of resveratrol as a new selective aryl hydrocarbon receptor, Med. Chem. Res. 17 (2008), pp. 212–218. doi:10.1007/s00044-007-9055-2.
Y., Xing, M., Nukaya, K.A., Satyshur, L., Jiang, V., Stanevich, E.N., Korkmaz, L., Burdette, G.D., Kennedy, Q., Cui, and C.A., Bradfield, Identification of the Ah-receptor structural determinants for ligand preferences, Toxicol. Sci. 129 (2012), pp. 86–97. doi:10.1093/toxsci/kfs194.
K., Bekki, H., Takigami, G., Suzuki, N., Tang, and K., Hayakawa, Evaluation of toxic activities of polycyclic aromatic hydrocarbon derivatives using in vitro bioassays, J. Health Sci. 55 (2009), pp. 601–610. doi:10.1248/jhs.55.601.
C., Gu, X., Ju, X., Jiang, K., Yu, S., Yang, and C., Sun, Improved 3D-QSAR analyzes for the predictive toxicology of polybrominated diphenyl ethers with CoMFA/CoMSIA and DFT, Ecotoxicol. Environ. Saf. 73 (2010), pp. 1470–1479. doi:10.1016/j.ecoenv.2009.11.003.
C.R., Martinez and B.L., Iverson, Rethinking the term “pi-stacking,” Chem. Sci. 3 (2012), pp. 2191–2201.
R.C., Kolanczyk, J.S., Denny, B.R., Sheedy, P.K., Schmieder, and M.A., Tapper, Estrogenic activity of multicyclic aromatic hydrocarbons in rainbow trout (Oncorhynchus mykiss) in vitro assays, Aquat. Toxicol. (2019), pp. 43–51. doi:10.1016/j.aquatox.2018.11.023.
C., Yun, J.A., Weiner, D.S., Chun, J., Yun, R.W., Cook, M.S., Schallmo, A.S., Kannan, S.M., Mitchell, R.D., Freshman, C., Park, W.K., Hsu, and E.L., Hsu, Mechanistic insight into the effects of Aryl hydrocarbon receptor activation on osteogenic differentiation, Bone Rep. 6 (2017), pp. 51–59. doi:10.1016/j.bonr.2017.02.003.
C.A., McQueen (ed.), Comprehensive Toxicology, 3rd ed., Vol. 35, Elsevier, Oxford, UK, 2018.