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  1. Endocrine Disruptor Knowledge Base

EDKB Publications

Publication Year

2013

  • Shen, J., Zhang, W., Fang, H., Perkins, R., Tong, W., and Hong, H. 2013. Homology modeling, molecular docking, and molecular dyamics simulations elucidated α-fetoprotein binding modes. BMC Bioinformatics. 14 (Suppl 14):S6 Abstract
  • 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. 2013. EADB: An Estrogenic Activity Database for Assessing Potential Endocrine Activity. Toxicological Sciences. 135 (2), 277-291 Abstract

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2012

  • Hong, H., Branham, W. S., Dial, S. L., Moland, C. L., Fang, H., Shen, J., and Perkins, R. 2012. Rat α-Fetoprotein binding affinities of a large set of structurally diverse chemicals elucidated the relantionships between structures and binding affinities. Chemical research in toxicology. 25 (11), 2553-2566 Abstract
  • Hong, H., Slavov, S., Ge, W., Qian, F., Su, Z., Fang, H., Cheng, Y., Perkins, R., and Shi, L. 2012. Mold2 Molecular Descriptors for QSAR. Statistical Modelling of Molecular Descriptors in QSAR/QSPR, Volume 2, 65-109 Abstract

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2010

  • Ding, D., Xu, L., Fang, H., Hong, H., Perkins, R., Harris, S., Bearden, D., Shi, L., and Tong, W. 2010. The EDKB: an Established Knowledge Base for Endocrine Disrupting Chemicals. BMC Bioinformatics. 11(Suppl 6):S5. Abstract

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2009

  • Fang, H., Perkins, R., Shi, L. Sheehan, D.M., and Tong, W. 2009. The FDA’s Endocrine Disruptor Knowledge Base (EDKB) — lessons learned in QSAR modeling and applications. In QSAR models designed for endocrine disruption. Edited by James Devillers. CRC Press. New York, London, Boca Raton. 6:143-171. Abstract

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2008

  • Hong, H., Xie, Q., Ge, W., Qian, F., Fang, F., Shi, L., Su, Z., Perkins, R., and Tong, W. 2008. Mold2, molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics. Journal of Chemical Information and Modeling. 48(7):1337–1344. Abstract

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2007

  • Welsh, W.J., Tong, W., Fang, H., and Georgopoulos, P. 2007. Toxicoinformatics: an introduction. 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.

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2005

  • Hong, H., Tong, W., Xie, Q., Fang, H., and Perkins, R. 2005. An in silico ensemble method for lead discovery: decision forest. SAR and QSAR in Environmental Research.16(4):339–347. Abstract
  • Tong, W., Hong, H., Fang, H., Xie, Q., and Perkins, R. 2005. From Decision Tree to Decision Forest – a novel chemometrics approach for structure activity relationship modeling. In Chemometrics and Chemoinformatics. Edited by Barry K. Lavine, ACS. Washington, DC. 894:173-185.

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2004

  • Beger, R., Young, J.F., and Fang, H. 2004. Discriminant function analyses of liver-specific carcinogens. Journal of Chemical Information and Computer Sciences. 44:1107-1110. Abstract
  • Tong, W., Fang, H., Hong, H., Xie, Q., Perkins, R., and Sheehan, D. 2004. Receptor-mediated toxicity: QSARs for estrogen receptor binding and priority setting of potential sestrogenic endocrine disruptors. 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.
  • Tong, W., Xie, Q., Hong, H., Fang, H., Shi, L., and Perkins, R. 2004. Assessment of prediction confidence and domain extrapolation of two structure-activity relationship models for predicting estrogen receptor binding activity. Environmental Health Perspectives.112(12). Abstract
  • Tong, W., Xie, Q., Hong, H., Fang, H., Shi, L., Perkins, R. 2004. A QSAR got to know its limitation: The importance of prediction confidence and application domain in Decision Forest for regulatory application. Environmental Health Perspectives. 112(12).  
  • Votano, J.R., Parham, M., Hall, L.H., Kier, L.B., Oloff, S., Tropsha, A., Xie, Q., and Tong, W. 2004. Three new consensus QSAR models for the prediction of Ames genotoxicity. Mutagenesis.19(5):365-377. Abstract

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2003

  • Fang, H., Tong, W., Branham, W., Moland, C.L., Dial, S.L., Hong, H., Xie, Q., Perkins, R., Owens, W., and Sheehan, D.M. 2003. Study of 202 natural, synthetic and environmental chemicals for binding to the androgen receptor. Chemical Research in Toxicology.16:1338-1358. Abstract
  • Fang, H., Tong, W., Welsh, W., and Sheehan, D.M. 2003. QSAR models in receptor-mediated effects: the nuclear receptor superfamily. Journal of Molecular Structure (THEOCHEM).622:113-125. Abstract
  • Hong, H., Fang, H., Xie, Q., Perkins, R., Sheehan, D.M., and Tong, W. 2003. Comparative Molecular Field Analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor. SAR/QSAR Environmental Research.14(5-6):373-388. Abstract
  • Perkins, R., Fang, H., Tong, W., and Welsh, W. 2003. Quantitative structure-activity relationship methods: perspectives on drug discovery and toxicology. Environmental Toxicology and Chemistry.22(8):1666-1679. Abstract
  • Tong, W., Fang, H., Hong, H., Xie, Q., Perkins, R., Anson, J., and Sheehan, D. 2003. Regulatory application of SAR/QSAR for priority setting of endocrine disruptors–a perspective. Pure and Applied Chemistry. 75(11-12):2375-2388. 
  • Tong, W., Hong, H., Fang, H., Xie, Q., and Perkins, R. 2003. Decision Forest: combining the predictions of multiple independent decision tree models. Journal of Chemical Information and Computer Sciences.43(2):525-531. Abstract
  • Tong, W., Welsh, W., Shi, L., Fang, H., and Perkins, R. 2003. Structure-activity relationship approaches and applications. Environmental Toxicology and Chemistry.22(8):1680-1695. Abstract
  • Walker, J.D., Fang, H., Perkins, R., and Tong, W. 2003. QSARs for endocrine disruption priority setting database 2: the integrated 4-phase model. QSAR & Combinatorial Science.22(1):89-105. Abstract

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2002

  • 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. 2002. Phytoestrogen and mycoestrogen bind to the rat uterine estrogen receptor. Journal of Nutrition.132(4):658-664. Abstract
  • 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. 2001. Structure-activity relationships for a large diverse set of natural, synthetic and environmental estrogens. Chemical Research in Toxicology. 14(3):280-294. 
  • Hong, H., Tong, W., Fang, H., Shi, L., Xie, Q., Wu, J., Perkins, R., Walker, J.D., Branham, W., and Sheehan, D. 2002. Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts. Environmental Health Perspectives.110(1):29-36. Abstract
  • Shi, L.M., Tong, W., Fang, H., Perkins, R., Wu, J., Tu, M., Blair, R., Branham, W., Waller, C., Walker, J., and Sheehan, D. 2002. An integrated "4-Phase" approach for setting endocrine disruption screening priorities — Phase I and II predictions of estrogen receptor binding affinity. SAR/QSAR Environmental Research.13(1):69-88. Abstract
  • Shi, L., Fang, H., Tong, W., Wu. J., Perkins, R., Blair, R., Branham, W., Dial, S.L., Moland, C.L., and Sheehan, D. 2001. QSAR models using a large diverse set of estrogens, Journal of Chemical Information and Computer Sciences. 41(1):186-195. 
  • Tong, W., Perkins, R., Fang, H., Hong, H., Xie, Q., Branham, W., Sheehan, D., and Anson, J. 2002. Development of quantitative structure-activity relationships (QSARs) and their use for priority setting in the testing strategy of endocrine disruptors. Regulatory Research Perspectives.1(3):1-16. PDF
  • Yu, S.J., Keenan, S.M., Tong, W., and Welsh, W.J. 2002. 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. Chemical Research in Toxicology.15(10): 1229-1234. Abstract

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2001

  • Blair, R., Fang, H., Gaylor, D., and Sheehan, D.M. 2001. Threshold analysis of selected dose-response data for endocrine active chemicals. Acta Pathologica, Microbiologica et Immunologica Scandinavica (APMIS).109:198-208(2001). Abstract
  • 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. 2001. Structure-activity relationships for a large diverse set of natural, synthetic and environmental estrogens. Chemical Research in Toxicology.14(3):280-294. Abstract
  • Shi, L.M., Fang, H., Tong, W., Wu, J., Perkins, R., Blair, R., Branham, W., Dial, S.L., Moland, C.L., and Sheehan, D. 2001. QSAR models using a large diverse set of estrogens. Journal of Chemical Information and Computer Sciences.41(1):186-195. Abstract

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2000

  • Fang, H, Tong, W., Perkins, R., Soto, A., Prechtl, N., and Sheehan, D.M. 2000. Quantitative comparison of in vitro assays for estrogenic activities. Environmental Health Perspectives.108(8):723-729. Abstract
  • 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. 2000. The estrogen receptor relative binding affinities of 188 natural and xenochemicals: structural diversity of ligands. Toxicological Sciences.54:138-153. Abstract

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1999

  • Tong, W., Perkins, R., and Sheehan, D.M. 1999. Perspectives on three-dimensional quantitative structure-activity relationship (3D-QSAR)/comparative Molecular Field Analysis (CoMFA) in determining estrogenic effects. Japan Chemistry Today.2:50-57.
  • Tong, W., Perkins, R., Wu, J., Shi, L., Tu, M., Fang, H., Blair, R., Branham, W., and Sheehan, D.M. 1999. An integrated computational approach for prioritizing potential estrogens. Yokohama Workshop on Environmental Endocrine Disruptors '99: Possible Effect on Human and Wildlife. p.247-254.
  • Xing, L., Welsh, W.J., Tong, W., Perkins, R., and Sheehan, D.M. 1999. Comparison of estrogen receptor alpha and beta subtypes based on comparative molecular field analysis (CoMFA). SAR and QSAR in Environmental Research.10:215-237. Abstract

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1998

  • Tong, W., Collantes, E.R., Welsh, W.J., Berglund, B., and Howlett, A. 1998. Derivation of a Pharmacophore Model for anandamide using constrained conformational searching and Comparative Molecular Field Analysis (CoMFA). Journal of Medicinal Chemistry.41:4207-4215. Abstract
  • Tong, W., Lowis, D.R., Perkins, R., Chen, Y., Welsh, W.J., Goddette, D.W., Heritage, T.W., and Sheehan, D.M. 1998. Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor. Journal of Chemical Information and Computer Sciences.38:669-77. Abstract

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1997

  • Tong, W., Perkins, R., Strelitz, R., Collantes, E.R., Keenan, S., Welsh, W.J., Branham, W.S., Sheehan, D.M. 1997. Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species. Environmental Health Perspectives.105:1116-24. Abstract
  • Tong, W., Perkins, R., Xing, L., Welsh, W.J., Sheehan, D.M. 1997. QSAR models for binding of estrogenic compounds to estrogen receptor alpha and beta subtypes. Endocrine.138:4022-5. Abstract

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Contact Information

Please address any questions and suggestions to Dr. Weida Tong at 870-543-7142 or [email protected].

EDKB is a product designed and produced by the National Center for Toxicological Research (NCTR). FDA and NCTR retain ownership of this product.

 

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