EDKB Publications
Endocrine Disruptor Knowledge Database (EDKB) Publications by year 1997-2022 with links to abstracts.
Publication Year
2009
2008
2007
2005
2004
2003
2002
2001
2000
1999
1998
1997
2021
- Structures of Endocrine-Disrupting Chemicals Correlate with the Activation of 12 Classic Nuclear Receptors.
Tan H., Chen Q., Hong H., Benfenati E., Gini G.C., Zhang X., Yu H., and Shi W.
Environ Sci Technol. 2021, 55(24):16552-16562. doi: 10.1021/acs.est.1c04997. Epub 2021 Dec 3. - Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations.
Sakkiah S., Selvaraj C., Guo W., Liu J., Ge W., Patterson T.A., and Hong H.
Int J Mol Sci. 2021, 22(17):9371. doi: 10.3390/ijms22179371.
2020
- CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.
Mansouri K.., Kleinstreuer N., Abdelaziz A.M., Alberga D., Alves V.M., Andersson P.L., Andrade C.H., Bai F., Balabin I., Ballabio D., Benfenati E., Bhhatarai B., Boyer S., Chen J., Consonni V., Farag S., Fourches D., García-Sosa A.T., Gramatica P., Grisoni F., Grulke C.M., Hong H., Horvath D., Hu X., Huang R., Jeliazkova N., Li J., Li X., Liu H., Manganelli S., Mangiatordi G.F., Maran U., Marcou G., Martin T., Muratov E., Nguyen D.T., Nicolotti O., Nikolov N.G., Norinder U., Papa E., Petitjean M., Piir G., Pogodin P., Poroikov V., Qiao X., Richard A.M., Roncaglioni A., Ruiz P., Rupakheti C., Sakkiah S., Sangion A., Schramm K.W., Selvaraj C., Shah I., Sild S., Sun L., Taboureau O., Tang Y., Tetko I.V., Todeschini R., Tong W., Trisciuzzi D., Tropsha A., Van Den Driessche G., Varnek A., Wang Z., Wedebye E.B., Williams A.J., Xie H., Zakharov A.V., Zheng Z., and Judson R.S.
Environ Health Perspect. 2020, 128(2):27002. doi: 10.1289/EHP5580. Epub 2020 Feb 7. - Structures of Endocrine-Disrupting Chemicals Determine Binding to and Activation of the Estrogen Receptor α and Androgen Receptor.
Tan H., Wang X., Hong H., Benfenati E., Giesy J.P., Gini G.C., Kusko R., Zhang X., Yu H., and Shi W.
Environ Sci Technol. 2020, 54(18):11424-11433. doi: 10.1021/acs.est.0c02639. Epub 2020 Aug 13. Erratum in: Environ Sci Technol. 2022, 56(5):3299.
2018
- Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.
Selvaraj C., Sakkiah S., Tong W., and Hong H.
Food Chem Toxicol. 2018, 112:495-506. doi: 10.1016/j.fct.2017.08.028. Epub 2017 Aug 24. - Computational prediction models for assessing endocrine disrupting potential of chemicals.
Sakkiah S., Guo W., Pan B., Kusko R., Tong W., and Hong H.
J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018, 36(4):192-218. doi: 10.1080/10590501.2018.1537132. Epub 2019 Jan 11.
2017
- Endocrine Disrupting Chemicals Mediated through Binding Androgen Receptor Are Associated with Diabetes Mellitus.
Sakkiah S., Wang T., Zou W., Wang Y., Pan B., Tong W., and Hong H.
Int J Environ Res Public Health. 2017, 15(1):25. doi: 10.3390/ijerph15010025. - Development of estrogen receptor beta binding prediction model using large sets of chemicals.
Sakkiah S., Selvaraj C., Gong P., Zhang C., Tong W., and Hong H.
Oncotarget. 2017, 8(54):92989-93000. doi: 10.18632/oncotarget.21723.
2016
- Structures of androgen receptor bound with ligands: advancing understanding of biological functions and drug discovery.
Sakkiah S., Ng H.W., Tong W., and Hong H.
Expert Opin Ther Targets. 2016, 20(10):1267-82. doi: 10.1080/14728222.2016.1192131. Epub 2016 May 31. - CERAPP: Collaborative Estrogen Receptor Activity Prediction Project.
Mansouri K., Abdelaziz A., Rybacka A., Roncaglioni A., Tropsha A., Varnek A., Zakharov A., Worth A., Richard A.M., Grulke C.M., Trisciuzzi D., Fourches D., Horvath D., Benfenati E., Muratov E., Wedebye E.B., Grisoni F., Mangiatordi G.F., Incisivo G.M., Hong H., Ng H.W., Tetko I.V., Balabin I., Kancherla J., Shen J., Burton J., Nicklaus M., Cassotti M., Nikolov N.G., Nicolotti O., Andersson P.L., Zang Q., Politi R., Beger R.D., Todeschini R., Huang R., Farag S., Rosenberg S.A., Slavov S., Hu X., and Judson R.S.
Environ Health Perspect. 2016, 124(7):1023-33. doi: 10.1289/ehp.1510267. Epub 2016 Feb 23. - Pathway Analysis Revealed Potential Diverse Health Impacts of Flavonoids that Bind Estrogen Receptors.
Ye H., Ng H.W., Sakkiah S., Ge W., Perkins R., Tong W., and Hong H.
Int J Environ Res Public Health. 2016, 13(4):373. doi: 10.3390/ijerph13040373. - Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products.
Hong H., Rua D., Sakkiah S., Selvaraj C., Ge W., and Tong W.
Int J Environ Res Public Health. 2016, 13(10):958. doi: 10.3390/ijerph13100958. - Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A.
Hong H., Harvey B.G., Palmese G.R., Stanzione J.F., Ng H.W., Sakkiah S., Tong W., and Sadler J.M.
Int J Environ Res Public Health. 2016 Jul 12;13(7):705. doi: 10.3390/ijerph13070705. - A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.
Hong H., Shen J., Ng H.W., Sakkiah S., Ye H., Ge W., Gong P., Xiao W., and Tong W.
Int J Environ Res Public Health. 2016, 13(4):372. doi: 10.3390/ijerph13040372. - QSAR Models at the US FDA/NCTR.
Hong H., Chen M., Ng H.W., and Tong W.
Methods Mol Biol. 2016, 1425:431-59. doi: 10.1007/978-1-4939-3609-0_18.
2015
- Human sex hormone-binding globulin binding affinities of 125 structurally diverse chemicals and comparison with their binding to androgen receptor, estrogen receptor, and α-fetoprotein.
Hong H., Branham W.S., Ng H.W., Moland C.L., Dial S.L., Fang H., Perkins R., Sheehan D., and Tong W.
Toxicol Sci. 2015, 143(2):333-48. doi: 10.1093/toxsci/kfu231. Epub 2014 Oct 27. - Estrogenic activity data extraction and in silico prediction show the endocrine disruption potential of bisphenol A replacement compounds.
Ng H.W., Shu M., Luo H., Ye H., Ge W., Perkins R., Tong W., and Hong H.
Chem Res Toxicol. 2015, 28(9):1784-95. doi: 10.1021/acs.chemrestox.5b00243. Epub 2015 Sep 2.
2014
- Versatility or promiscuity: the estrogen receptors, control of ligand selectivity and an update on subtype selective ligands.
Ng H.W., Perkins R., Tong W., and Hong H.
Int J Environ Res Public Health. 2014, 11(9):8709-42. doi: 10.3390/ijerph110908709. - Competitive molecular docking approach for predicting estrogen receptor subtype α agonists and antagonists.
Ng H.W., Zhang W., Shu M., Luo H., Ge W., Perkins R., Tong W., and Hong H.
BMC Bioinformatics. 2014, 15 Suppl 11(Suppl 11):S4. doi: 10.1186/1471-2105-15-S11-S4. Epub 2014 Oct 21.
2013
- Homology modeling, molecular docking, and molecular dyamics simulations elucidated α-fetoprotein binding modes.
Shen J., Zhang W., Fang H., Perkins R., Tong W., and Hong H.
BMC Bioinformatics. 14 (Suppl 14):S6. - EADB: An Estrogenic Activity Database for Assessing Potential Endocrine Activity.
Shen J., Xu L., Fang H., Richard A.M., Bray J.D., Judson R.S., Zhou G., Colatsky T.J., Aungst J.L., Teng C., Harris S.C., Ge W., Dai S.Y., Su Z., Jacobs A.C., Harrouk W., Perkins R., Tong W., and Hong H.
Toxicological Sciences. 135 (2), 277-291.
2012
- Rat α-Fetoprotein binding affinities of a large set of structurally diverse chemicals elucidated the relantionships between structures and binding affinities.
Hong H., Branham W.S., Dial S.L., Moland C.L., Fang H., Shen J., and Perkins R.
Chemical Research in Toxicology. 25 (11), 2553-2566. - Mold2 Molecular Descriptors for QSAR.
Hong H., Slavov S., Ge W., Qian F., Su Z., Fang H., Cheng Y., Perkins R., and Shi L.
Statistical Modelling of Molecular Descriptors in QSAR/QSPR, Volume 2, 65-109.
2010
- The EDKB: an Established Knowledge Base for Endocrine Disrupting Chemicals.
Ding D., Xu L., Fang H., Hong H., Perkins R., Harris S., Bearden D., Shi L., and Tong W.
BMC Bioinformatics. 11(Suppl 6):S5.
2009
- The FDA’s Endocrine Disruptor Knowledge Base (EDKB) — lessons learned in QSAR modeling and applications.
Fang H., Perkins R., Shi L. Sheehan D.M., and Tong W.
In QSAR Models Designed for Endocrine Disruption.
Edited by James Devillers. CRC Press. New York, London, Boca Raton. 2009, 6:143-171.
2008
- Mold2, molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics.
Hong H., Xie Q., Ge W., Qian F., Fang F., Shi L., Su Z., Perkins R., and Tong W.
Journal of Chemical Information and Modeling. 48(7):1337–1344.
2007
- Toxicoinformatics: an introduction.
Welsh W.J., Tong W., Fang H., and Georgopoulos P.
In Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals.
Edited by Sean Ekins, Wiley. New York, Chichester, Weinheim, Brisbane, Singapore, Toronto. 6:153-182.
2005
- An in silico ensemble method for lead discovery: decision forest.
Hong H., Tong W., Xie Q., Fang H., and Perkins R.
SAR and QSAR in Environmental Research. 16(4):339–347. - From Decision Tree to Decision Forest – a novel chemometrics approach for structure activity relationship modeling.
Tong W., Hong H., Fang H., Xie Q., and Perkins R.
In Chemometrics and Chemoinformatics.
Edited by Barry K. Lavine, ACS. Washington, DC. 2005, 894:173-185.
2004
- Discriminant function analyses of liver-specific carcinogens.
Beger R., Young J.F., and Fang H.
Journal of Chemical Information and Computer Sciences. 44:1107-1110. - Receptor-mediated toxicity: QSARs for estrogen receptor binding and priority setting of potential sestrogenic endocrine disruptors.
Tong W., Fang H., Hong H., Xie Q., Perkins R., and Sheehan D.
In Predicting Chemical Toxicity and Fate. Edited by Mark T.D. Cronin and David J. Livingstone. CRC Press, New York, London, Boca Raton. Chapter 13. - Assessment of prediction confidence and domain extrapolation of two structure-activity relationship models for predicting estrogen receptor binding activity.
Tong W., Xie Q., Hong H., Fang H., Shi L., and Perkins R.
Environmental Health Perspectives. 112(12). - Three new consensus QSAR models for the prediction of Ames genotoxicity.
Votano J.R., Parham M., Hall L.H., Kier L.B., Oloff S., Tropsha A., Xie Q., and Tong W.
Mutagenesis. 19(5):365-377.
2003
- Study of 202 natural, synthetic and environmental chemicals for binding to the androgen receptor.
Fang H., Tong W., Branham W., Moland C.L., Dial S.L., Hong H., Xie Q., Perkins R., Owens W., and Sheehan D.M.
Chemical Research in Toxicology. 16:1338-1358. - QSAR models in receptor-mediated effects: the nuclear receptor superfamily.
Fang H., Tong W., Welsh W., and Sheehan D.M.
Journal of Molecular Structure (THEOCHEM). 622:113-125. - Comparative Molecular Field Analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor.
Hong H., Fang H., Xie Q., Perkins R., Sheehan D.M., and Tong W.
SAR/QSAR Environmental Research. 14(5-6):373-388. - Quantitative structure-activity relationship methods: perspectives on drug discovery and toxicology.
Perkins R., Fang H., Tong W., and Welsh W.
Environmental Toxicology and Chemistry. 22(8):1666-1679. - Regulatory application of SAR/QSAR for priority setting of endocrine disruptors–a perspective.
Tong W., Fang H., Hong H., Xie Q., Perkins R., Anson J., and Sheehan D.
Pure and Applied Chemistry. 75(11-12):2375-2388. - Decision Forest: combining the predictions of multiple independent decision tree models.
Tong W., Hong H., Fang H., Xie Q., and Perkins R.
Journal of Chemical Information and Computer Sciences. 43(2):525-531. - Structure-activity relationship approaches and applications.
Tong W., Welsh W., Shi L., Fang H., and Perkins R.
Environmental Toxicology and Chemistry. 22(8):1680-1695. - QSARs for endocrine disruption priority setting database 2: the integrated 4-phase model.
Walker J.D., Fang H., Perkins R., and Tong W.
QSAR & Combinatorial Science. 22(1):89-105.
2002
- Phytoestrogen and mycoestrogen bind to the rat uterine estrogen receptor.
Branham W.S., Dial S.L., Moland C.L., Hass B., Blair R., Fang H., Shi L., Tong W., Perkins R., and Sheehan D.M.
Journal of Nutrition. 132(4):658-664. - Structure-activity relationships for a large diverse set of natural, synthetic and environmental estrogens.
Fang H., Tong W., Shi L., Blair R., Perkins R., Branham W.S., Hass B.S., Xie Q., Dial S.L., Moland C.L., and Sheehan D.M.
Chemical Research in Toxicology. 2001, 14(3):280-294. - Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts.
Hong H., Tong W., Fang H., Shi L., Xie Q., Wu J., Perkins R., Walker J.D., Branham W., and Sheehan D.
Environmental Health Perspectives. 110(1):29-36. - An integrated "4-Phase" approach for setting endocrine disruption screening priorities — Phase I and II predictions of estrogen receptor binding affinity.
Shi L.M., Tong W., Fang H., Perkins R., Wu J., Tu M., Blair R., Branham W., Waller C., Walker J., and Sheehan D.
SAR/QSAR Environmental Research. 13(1):69-88. - QSAR models using a large diverse set of estrogens.
Shi L., Fang H., Tong W., Wu J., Perkins R., Blair R., Branham W., Dial S.L., Moland C.L., and Sheehan D.
Journal of Chemical Information and Computer Sciences. 2001, 41(1):186-195. - Development of quantitative structure-activity relationships (QSARs) and their use for priority setting in the testing strategy of endocrine disruptors.
Tong W., Perkins R., Fang H., Hong H., Xie Q., Branham W., Sheehan D., and Anson J.
Regulatory Research Perspectives. 2002, 1(3):1-16. PDF - Influence of the structural diversity of data sets on the statistical quality of three-dimensional quantitative structure-activity relationship (3D-QSAR) models: predicting the estrogenic activity of xenoestrogens.
Yu S.J., Keenan S.M., Tong W., and Welsh W.J.
Chemical Research in Toxicology. 15(10): 1229-1234.
2001
- Threshold analysis of selected dose-response data for endocrine active chemicals.
Blair R., Fang H., Gaylor D., and Sheehan D.M.
Acta Pathologica, Microbiologica et Immunologica Scandinavica (APMIS). 109:198-208(2001). - Structure-activity relationships for a large diverse set of natural, synthetic and environmental estrogens.
Fang H., Tong W., Shi L., Blair R., Perkins R., Branham W.S., Hass B.S., Xie Qian, Dial S.L., Moland C.L., and Sheehan D.M.
Chemical Research in Toxicology. 14(3):280-294. - QSAR models using a large diverse set of estrogens.
Shi L.M., Fang H., Tong W., Wu J., Perkins R., Blair R., Branham W., Dial S.L., Moland C.L., and Sheehan D.
Journal of Chemical Information and Computer Sciences. 41(1):186-195.
2000
- Quantitative comparison of in vitro assays for estrogenic activities.
Fang H, Tong W., Perkins R., Soto A., Prechtl N., and Sheehan D.M.
Environmental Health Perspectives. 108(8):723-729. - The estrogen receptor relative binding affinities of 188 natural and xenochemicals: structural diversity of ligands.
Blair R., Fang H., Branham W.S., Hass B., Dial S.L., Moland C.L., Tong W., Shi L., Perkins R., and Sheehan D.M.
Toxicological Sciences. 54:138-153.
1999
- An integrated computational approach for prioritizing potential estrogens.
Tong W., Perkins R., Wu J., Shi L., Tu M., Fang H., Blair R., Branham W., and Sheehan D.M.
Yokohama Workshop on Environmental Endocrine Disruptors '99: Possible Effect on Human and Wildlife. 1999, 247-254. - Comparison of estrogen receptor alpha and beta subtypes based on comparative molecular field analysis (CoMFA).
Xing L., Welsh W.J., Tong W., Perkins R., and Sheehan D.M.
SAR and QSAR in Environmental Research.10:215-237.
1998
- Derivation of a Pharmacophore Model for anandamide using constrained conformational searching and Comparative Molecular Field Analysis (CoMFA).
Tong W., Collantes E.R., Welsh W.J., Berglund B., and Howlett A.
Journal of Medicinal Chemistry. 41:4207-4215. - Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor.
Tong W., Lowis D.R., Perkins R., Chen Y., Welsh W.J., Goddette D.W., Heritage T.W., and Sheehan D.M.
Journal of Chemical Information and Computer Sciences. 38:669-77.
1997
- Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species.
Tong W., Perkins R., Strelitz R., Collantes E.R., Keenan S., Welsh W.J., Branham W.S., and Sheehan D.M.
Environmental Health Perspectives.105:1116-24. - QSAR models for binding of estrogenic compounds to estrogen receptor alpha and beta subtypes.
Tong W., Perkins R., Xing L., Welsh W.J., and Sheehan D.M.
Endocrine.138:4022-5.
Contact Information
Please address any questions and suggestions to Dr. Weida Tong at 870-543-7142 or weida.tong@fda.hhs.gov.
EDKB is a product designed and produced by the National Center for Toxicological Research (NCTR). FDA and NCTR retain ownership of this product.