Assessing the chemical-induced estrogenicity using in silico and in vitro methods

[en] Multiple substances are considered endocrine disrupting chemicals (EDCs). However, there is a significant gap in the early prioritization of EDC’s effects. In this work, in silico and in vitro methods were used to model estrogenicity. Two Quantitative Structure-Activity Relationship (QSAR) models based on Logistic Regression and REPTree algorithms were built using a large and diverse database of estrogen receptor (ESR) agonism. A 10-fold external validation demonstrated their robustness and predictive capacity. Mechanistic interpretations of the molecular descriptors (C-026, nArOH,PW5, B06[Br-Br]) used for modelling suggested that the heteroatomic fragments, aromatic hydroxyls, and bromines, and the relative bond accessibility areas of molecules, are structural determinants in estrogenicity. As validation of the QSARs, ESR transactivity of thirteen persistent organic pollutants (POPs) and suspected EDCs was tested in vitro using the MMV-Luc cell line. A good correspondence between predictions and experimental bioassays demonstrated the value of the QSARs for prioritization of ESR agonist compounds.

Disciplines :

Biochemistry, biophysics & molecular biology

Author, co-author :

Goya-Jorge, Elizabeth ; Université de Liège - ULiège > Département de sciences des denrées alimentaires (DDA) > Gestion de la qualité dans la chaîne alimentaire

Amber, Mazia; Queen's University Belfast

Gozalbes, Rafael; ProtoQSAR SL

Connolly, Lisa; Queen's University Belfast

Barigye, Stephen J

Language :

English

Title :

Assessing the chemical-induced estrogenicity using in silico and in vitro methods

Publication date :

10 June 2021

Journal title :

Environmental Toxicology and Pharmacology

ISSN :

1382-6689

Publisher :

Elsevier, Netherlands

Volume :

Pages :

103688

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://doi.org/10.1016/j.etap.2021.103688

European Projects :

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

Funders :

CE - Commission Européenne [BE]

Available on ORBi :

since 14 July 2021

Statistics

Number of views

39 (2 by ULiège)

Number of downloads

1 (1 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

Bibliography

Asikainen, A.H., Ruuskanen, J., Tuppurainen, K.A., Consensus kNN QSAR: A versatile method for predicting the estrogenic activity of organic compounds in silico. A comparative study with five estrogen receptors and a large, diverse set of ligands. Environ. Sci. Technol. 38 (2004), 6724–6729, 10.1021/es049665h.
Berntsen, H.F., Berg, V., Thomsen, C., Ropstad, E., Zimmer, K.E., 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), 1002–1016, 10.1080/15287394.2017.1354439.
Chen, D., Hale, R.C., A global review of polybrominated diphenyl ether flame retardant contamination in birds. Environ. Int. 36 (2010), 800–811, 10.1016/j.envint.2010.05.013.
Cherkasov, A., Muratov, E.N., Fourches, D., Varnek, A., Baskin, I.I., Cronin, M., Dearden, J., Gramatica, P., Martin, Y.C., Todeschini, R., Consonni, V., Kuz'Min, V.E., Cramer, R., Benigni, R., Yang, C., Rathman, J., Terfloth, L., Gasteiger, J., Richard, A., Tropsha, A., QSAR modeling: Where have you been? Where are you going to?. J. Med. Chem. 57 (2014), 4977–5010, 10.1021/jm4004285.
Christou, M., Fraser, T.W.K., Berg, V., Ropstad, E., Kamstra, J.H., Calcium signaling as a possible mechanism behind increased locomotor response in zebrafish larvae exposed to a human relevant persistent organic pollutant mixture or PFOS. Environ. Res., 187, 2020, 109702, 10.1016/j.envres.2020.109702.
Collet, B., van Vugt-Lussenburg, B.M.A., Swart, K., Helmus, R., Naderman, M., de Rijke, E., Eggesbø, M., Brouwer, A., van der Burg, B., Antagonistic activity towards the androgen receptor independent from natural sex hormones in human milk samples from the Norwegian HUMIS cohort. Environ. Int., 143, 2020, 105948, 10.1016/j.envint.2020.105948.
Connolly, L., Ropstad, E., Verhaegen, S., In vitro bioassays for the study of endocrine-disrupting food additives and contaminants. TrAC - Trends in Analytical Chemistry 30 (2011), 227–238, 10.1016/j.trac.2010.10.009.
Doan, T.Q., Berntsen, H.F., Verhaegen, S., Ropstad, E., Connolly, L., Igout, A., Muller, M., Scippo, M.L., A mixture of persistent organic pollutants relevant for human exposure inhibits the transactivation activity of the aryl hydrocarbon receptor in vitro. Environ. Pollut., 254, 2019, 10.1016/j.envpol.2019.113098.
Doan, T.Q., Connolly, L., Igout, A., Nott, K., Muller, M., Scippo, M.L., In vitro profiling of the potential endocrine disrupting activities affecting steroid and aryl hydrocarbon receptors of compounds and mixtures prevalent in human drinking water resources. Chemosphere, 258, 2020, 127332, 10.1016/j.chemosphere.2020.127332.
Eriksson, P., Jakobsson, E., Fredriksson, A., Brominated flame retardants: a novel class of developmental neurotoxicants in our environment?. Environ. Health Perspect. 109 (2001), 903–908, 10.1289/ehp.01109903.
Estrada, E., The structural interpretation of the randić index. Internet Electron. J. Mol. Des. 1 (2002), 360–366.
European Commission, Council Decision of 14 October 2004 Concerning the Conclusion, on Behalf of the European Community, of the Stockholm Convention on Persistent Organic Pollutants (2006/507/EC). 2006.
European Commission, 4th Report on the Implementation of the “Community Strategy for Endocrine Disrupters” a Range of Substances Suspected of Interfering With the Hormone Systems of Humans and Wildlife (COM (1999) 706)., 2011.
Frizzell, C., Ndossi, D., Verhaegen, S., Dahl, E., Eriksen, G., Sørlie, M., Ropstad, E., Muller, M., Elliott, C.T., Connolly, L., Endocrine disrupting effects of zearalenone, alpha- and beta-zearalenol at the level of nuclear receptor binding and steroidogenesis. Toxicol. Lett. 206 (2011), 210–217, 10.1016/j.toxlet.2011.07.015.
Futran Fuhrman, V., Tal, A., Arnon, S., Why endocrine disrupting chemicals (EDCs) challenge traditional risk assessment and how to respond. J. Hazard. Mater. 286 (2015), 589–611, 10.1016/j.jhazmat.2014.12.012.
Gao, Y., Li, X., Guo, L.-H., Assessment of estrogenic activity of perfluoroalkyl acids based on ligand-induced conformation state of human estrogen receptor. Environ. Sci. Technol. 47 (2013), 634–641, 10.1021/es304030x.
Goya-Jorge, E., de Julián-Ortiz, J., Gozalbes, R., Protection against endocrine disruption through quantitative structure-activity relationship modelling. Revista de Toxicología 37 (2020), 55–68.
Gregoraszczuk, E.L., Ptak, A., Endocrine-disrupting chemicals: some actions of POPs on female reproduction. Int. J. Endocrinol., 2013, 2013, 828532, 10.1155/2013/828532.
Guo, W., Pan, B., Sakkiah, S., Yavas, G., Ge, W., Zou, W., Tong, W., Hong, H., Persistent organic pollutants in food: contamination sources, health effects and detection methods. Int. J. Environ. Res. Public Health, 16, 2019, 10.3390/ijerph16224361.
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H., The WEKA data mining software: an update. SIGKDD Explor. 11 (2009), 10–18, 10.1145/1656274.1656278.
Hamilton, K.J., Hewitt, S.C., Arao, Y., Korach, K.S., Estrogen hormone biology. Curr. Top. Dev. Biol. 125 (2017), 109–146, 10.1016/bs.ctdb.2016.12.005.
Ji, L., Wang, X., Yang, X., Liu, S., Wang, L., Back-propagation network improved by conjugate gradient based on genetic algorithm in QSAR study on endocrine disrupting chemicals. Chinese Sci. Bull. 53 (2008), 33–39, 10.1007/s11434-007-0484-6.
Li, J., Gramatica, P., QSAR classification of estrogen receptor binders and pre-screening of potential pleiotropic EDCs. SAR QSAR Environ. Res. 21 (2010), 657–669, 10.1080/1062936X.2010.528254.
Li, F., Wu, H., Li, L., Li, X., Zhao, J., Peijnenburg, W.J.G.M., Docking and QSAR study on the binding interactions between polycyclic aromatic hydrocarbons and estrogen receptor. Ecotoxicol. Environ. Saf. 80 (2012), 273–279, 10.1016/j.ecoenv.2012.03.009.
Li, X., Ye, L., Xiaoxiang, Wang, Xinzhou, Wang, Liu, H., Qian, X., Zhu, Y., Yu, H., Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on estrogenic activity of hydroxylated polychlorinated biphenyls. Sci. Total Environ. 441 (2012), 230–238, 10.1016/j.scitotenv.2012.08.072.
McComb, J., Mills, I.G., Berntsen, H.F., Ropstad, E., Verhaegen, S., Connolly, L., Human-based exposure levels of perfluoroalkyl acids may induce harmful effects to health by disrupting major components of androgen receptor signalling in vitro. Expo. Health 12 (2020), 527–538, 10.1007/s12403-019-00318-8.
Meerts, I.A., Letcher, R.J., Hoving, S., Marsh, G., Bergman, A., Lemmen, J.G., van der Burg, B., Brouwer, A., In vitro estrogenicity of polybrominated diphenyl ethers, hydroxylated PDBEs, and polybrominated bisphenol A compounds. Environ. Health Perspect. 109 (2001), 399–407, 10.1289/ehp.01109399.
Ng, H.W., Doughty, S.W., Luo, H., Ye, H., Ge, W., Tong, W., Hong, H., Development and validation of decision forest model for estrogen receptor binding prediction of chemicals using large data sets. Chem. Res. Toxicol. 28 (2015), 2343–2351, 10.1021/acs.chemrestox.5b00358.
OECD, Guidance Document on the Validation of (Quantitative) Structure-Activity Relationship [(Q)SAR] Models, OECD Series on Testing and Assessment. 2014, OECD, 10.1787/9789264085442-en.
OECD, Test No. 455: Performance-Based Test Guideline for Stably Transfected Transactivation In Vitro Assays to Detect Estrogen Receptor Agonists and Antagonists. 2016, 10.1787/9789264265295-en.
Qiu, Z., Qu, K., Luan, F., Liu, Y., Zhu, Y., Yuan, Y., Li, H., Zhang, H., Hai, Y., Zhao, C., Binding specificities of estrogen receptor with perfluorinated compounds: a cross species comparison. Environ. Int., 134, 2020, 105284, 10.1016/j.envint.2019.105284.
Randić, M., Molecular shape profiles. J. Chem. Inf. Comput. Sci. 35 (1995), 373–382, 10.1021/ci00025a005.
Randić, M., Basak, S.C., Optimal molecular descriptors based on weighted path numbers. J. Chem. Inf. Comput. Sci. 39 (1999), 261–266, 10.1021/ci9800763.
Rashid, H., Alshahrani, S.S.A., Diet: a source of endocrine disruptors. Endocr. Metab. Immune Disord. - Drug Targets, 2020, 10.2174/1871530319666191022100141.
Rattenborg, T., Gjermandsen, I., Bonefeld-Jørgensen, E.C., Inhibition of E2-induced expression of BRCA1 by persistent organochlorines. Breast Cancer Res., 4, 2002, R12, 10.1186/bcr461.
Ren, J., Xiaoping, Wang, Wang, C., Gong, P., Wang, Xiruo, Yao, T., Biomagnification of persistent organic pollutants along a high-altitude aquatic food chain in the Tibetan Plateau: processes and mechanisms. Environ. Pollut. 220 (2017), 636–643, 10.1016/j.envpol.2016.10.019.
Ruiz, P., Sack, A., Wampole, M., Bobst, S., Vracko, M., Integration of in silico methods and computational systems biology to explore endocrine-disrupting chemical binding with nuclear hormone receptors. Chemosphere 178 (2017), 99–109, 10.1016/j.chemosphere.2017.03.026.
Saito, T., Rehmsmeier, M., The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. PLoS One 10 (2015), 1–21, 10.1371/journal.pone.0118432.
Salama, J., Chakraborty, T.R., Ng, L., Gore, A.C., Effects of polychlorinated biphenyls on estrogen receptor-beta expression in the anteroventral periventricular nucleus. Environ. Health Perspect. 111 (2003), 1278–1282, 10.1289/ehp.6126.
Shannon, M., Xie, Y., Verhaegen, S., Wilson, J., Berntsen, H.F., Zimmer, K.E., Ropstad, E., Green, B.D., Connolly, L., A human relevant defined mixture of persistent organic pollutants (POPs) affects in vitro secretion of glucagon-like peptide 1 (GLP-1), but does not affect translocation of its receptor. Toxicol. Sci. 172 (2019), 359–367, 10.1093/toxsci/kfz192.
Shekhar, P.V.M., Werdell, J., Basrur, V.S., Environmental Estrogen Stimulation of Growth and Estrogen Receptor Function in Preneoplastic and Cancerous Human Breast Cell Lines. JNCI: Journal of the National Cancer Institute 89 (1997), 1774–1782, 10.1093/jnci/89.23.1774.
Steenland, K., Fletcher, T., Savitz, D.A., Epidemiologic evidence on the health effects of perfluorooctanoic acid (PFOA). Environ. Health Perspect. 118 (2010), 1100–1108, 10.1289/ehp.0901827.
Thomsen, C., Stigum, H., Frøshaug, M., Broadwell, S.L., Becher, G., Eggesbø, M., Determinants of brominated flame retardants in breast milk from a large scale Norwegian study. Environ. Int. 36 (2010), 68–74, 10.1016/j.envint.2009.10.002.
Todeschini, R., Consonni, V., Handbook of Molecular Descriptors. 2009, Wiley-VCH, Weinheim, Germany.
Todeschini, R., Consonni, V., Mauri, A., Pavan, M., DRAGON—Software for the Calculation of Molecular Descriptors. 2007.
Wang, Z., Li, Y., Ai, C., Wang, Y., In Silico prediction of estrogen receptor subtype binding affinity and selectivity using statistical methods and molecular docking with 2-arylnaphthalenes and 2-arylquinolines. Int. J. Mol. Sci. 11 (2010), 3434–3458, 10.3390/ijms11093434.
Weiß, C.H., StatSoft, Inc., Tulsa, OK.: STATISTICA, version 8. Asta Adv. Stat. Anal. 91 (2007), 339–341, 10.1007/s10182-007-0038-x.
WHO/UNEP, State of the science of endocrine disrupting chemicals - 2012. An Assessment of the State of the Science of Endocrine Disruptors Prepared by a Group of Experts for the United Nations Environment Programme (UNEP) and WHO, 2013.
Willemsen, P., Scippo, M.-L., Kausel, G., Figueroa, J., Maghuin-Rogister, G., Martial, J.A., Muller, M., Use of reporter cell lines for detection of endocrine-disrupter activity. Anal. Bioanal. Chem. 378 (2004), 655–663, 10.1007/s00216-003-2217-2.
Yadav, A., Amber, M., Zosen, D., Labba, N.A., Huiberts, E.H.W., Samulin Erdem, J., Haugen, F., Berntsen, H.F., Zienolddiny, S., Paulsen, R.E., Ropstad, E., Connolly, L., Verhaegen, S., A human relevant mixture of persistent organic pollutants (POPs) and perfluorooctane sulfonic acid (PFOS) enhance nerve growth factor (NGF)-induced neurite outgrowth in PC12 cells. Toxicol. Lett. 338 (2021), 85–96, 10.1016/j.toxlet.2020.12.007.
Zang, Q., Rotroff, D.M., Judson, R.S., Binary classification of a large collection of environmental chemicals from estrogen receptor assays by quantitative structure-activity relationship and machine learning methods. J. Chem. Inf. Model. 53 (2013), 3244–3261, 10.1021/ci400527b.
Zhang, L., Sedykh, A., Tripathi, A., Zhu, H., Afantitis, A., Mouchlis, V.D., Melagraki, G., Rusyn, I., Tropsha, A., Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches. Toxicol. Appl. Pharmacol. 272 (2013), 67–76, 10.1016/j.taap.2013.04.032.
Zhang, Q., Yan, L., Wu, Y., Ji, L., Chen, Y., Zhao, M., Dong, X., A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals. Sci. Total Environ. 580 (2017), 1268–1275, 10.1016/j.scitotenv.2016.12.088.