Abstract
Purpose
In this study, two unreported estrogen antagonists were identified using a combination of computational screening and a simple bacterial estrogen sensor.
Methods
Molecules here presented were initially part of a group obtained from a library of over a half million chemical compounds, using the Shape Signatures method. The structures within this group were then clustered and compared to known antagonists based on their physico-chemical parameters, and possible binding modes of the compounds to the Estrogen Receptor α (ERα) were analyzed. Finally, thirteen candidate compounds were purchased, and two of them were shown to behave as potential subtype-selective estrogen antagonists using a set of bacterial estrogen biosensors, which included sensors for ERα, ERβ, and a negative control thyroid hormone β biosensor. These activities were then analyzed using an ELISA assay against activated ERα in human MCF-7 cell extract.
Results
Two new estrogen receptor antagonists were detected using in silico Shape Signatures method with an engineered subtype-selective bacterial estrogen biosensor and commercially available ELISA assay. Additional thyroid biosensor control experiments confirmed no compounds interacted with human thyroid receptor β.
Conclusions
This work demonstrates an effective combination of computational analysis and simple bacterial screens for rapid identification of potential hormone-like therapeutics.
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Abbreviations
- ANOVA:
-
Analysis of variance
- BPA:
-
Bisphenol A
- COMFA:
-
Comparative molecular field analysis
- DMSO:
-
Dimethylsulfoxide
- ELISA:
-
Enzyme-linked immunosorbent assay
- ERs:
-
Estrogen receptors
- E2:
-
17-β-estradiol
- GOLD:
-
Genetic optimization for ligand docking algorithm
- HBA:
-
Number of hydrogen bonding acceptors
- HBD:
-
Number of hydrogen bonding donors
- HRP:
-
Horseradish peroxide
- LB:
-
Luria-Bertani
- LBD:
-
Ligand binding domain
- logp:
-
Octanol-water partition coefficient
- MOE:
-
Molecular operation environment
- MEP:
-
Molecular electrostatic potential
- MW:
-
Molecular weights
- NCI:
-
National cancer institute
- NHR:
-
Nuclear hormone receptors
- NSC:
-
National service center
- OD:
-
Optical density
- pMIT::ER:
-
plasmid MBP (maltose-binding protein tag) -Intein-TS (thymidylate synthase)::Estrogen Receptor
- pMIT::TR:
-
plasmid MBP (maltose-binding protein tag) -Intein-TS (thymidylate synthase)::Thyroid Receptor
- PSA:
-
Polar surface area (Å2)
- QSAR:
-
Quantitative structure-activity relationship
- RB:
-
Number of rotatable bonds
- SERMs:
-
Selective estrogen receptor modulators
- TTM:
-
Medium which contain -Thy medium supplemented with 10 μg/ml trimethoprim and 50 μg/ml thymine
- UPGMA:
-
Unweighted pair group method with arithmetic means
- +THY:
-
A thymine-rich medium; used as a positive control
- -THY:
-
A thymine-free medium; used as a negative control
REFERENCES
Kuiper GG, Enmark E, Pelto-Huikko M, Nilsson S, Gustafsson JA. Cloning of a novel receptor expressed in rat prostate and ovary. Proc Natl Acad Sci U S A. 1996;93:5925–30.
Manas ES, Unwalla RJ, Xu ZB, Malamas MS, Miller CP, Harris HA, et al. Structure-based design of estrogen receptor-beta selective ligands. J Am Chem Soc. 2004;126:15106–19.
Pike AC, Brzozowski AM, Hubbard RE, Bonn T, Thorsell AG, Engstrom O, et al. Structure of the ligand-binding domain of oestrogen receptor beta in the presence of a partial agonist and a full antagonist. EMBO J. 1999;18:4608–18.
Tremblay A, Tremblay GB, Labrie C, Labrie F, Giguere V. EM-800, a novel antiestrogen, acts as a pure antagonist of the transcriptional functions of estrogen receptors alpha and beta. Endocrinology. 1998;139:111–8.
McDonnell DP. The molecular pharmacology of estrogen receptor modulators: implications for the treatment of breast cancer. Clin Cancer Res. 2005;11:871s–7s.
Jensen EV, Jordan VC. The estrogen receptor: a model for molecular medicine. Clin Cancer Res. 2003;9:1980–9.
Shiau AK, Barstad D, Radek JT, Meyers MJ, Nettles KW, Katzenellenbogen BS, et al. Structural characterization of a subtype-selective ligand reveals a novel mode of estrogen receptor antagonism. Nat Struct Biol. 2002;9:359–64.
Liu H, Lee ES, Deb Los Reyes A, Zapf JW, Jordan VC. Silencing and reactivation of the selective estrogen receptor modulator-estrogen receptor alpha complex. Cancer Res. 2001;61:3632–9.
Grese TA, Sluka JP, Bryant HU, Cullinan GJ, Glasebrook AL, Jones CD, et al. Molecular determinants of tissue selectivity in estrogen receptor modulators. Proc Natl Acad Sci U S A. 1997;94:14105–10.
Gauthier S, Caron B, Cloutier J, Dory YL, Favre A, Larouche D, et al. (S)-(+)-4-[7-(2, 2-dimethyl-1-oxopropoxy)-4-methyl-2-[4-[2-(1-piperidinyl)- ethoxy]phenyl]-2H–1-benzopyran-3-yl]-phenyl 2, 2-dimethylpropanoate (EM-800): a highly potent, specific, and orally active nonsteroidal antiestrogen. J Med Chem. 1997;40:2117–22.
Bentrem D, Dardes R, Liu H, MacGregor-Schafer J, Zapf J, Jordan V. Molecular mechanism of action at estrogen receptor alpha of a new clinically relevant antiestrogen (GW7604) related to tamoxifen. Endocrinology. 2001;142:838–46.
Fan M, Rickert EL, Chen L, Aftab SA, Nephew KP, Weatherman RV. Characterization of molecular and structural determinants of selective estrogen receptor downregulators. Breast Cancer Res Treat. 2007;103:37–44.
Zauhar RJ, Moyna G, Tian L, Li Z, Welsh WJ. Shape signatures: a new approach to computer-aided ligand- and receptor-based drug design. J Med Chem. 2003;46:5674–90.
Irwin JJ, Shoichet BK. ZINC—a free database of commercially available compounds for virtual screening. J Chem Inf Model. 2005;45:177–82.
Nagarajan K, Zauhar R, Welsh WJ. Enrichment of ligands for the serotonin receptor using the Shape Signatures approach. J Chem Inf Model. 2005;45:49–57.
GOLD. Cambridge, UK: Cambridge crystallographic data centre; 2004.
SILVER. Cambridge, UK: Cambridge crystallographic data centre; 2004.
Jones G, Willett P, Glen RC. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J Mol Biol. 1995;245:43–53.
Jones G, Willett P, Glen RC, Leach AR, Taylor R. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997;267:727–48.
Nissink JW, Murray C, Hartshorn M, Verdonk ML, Cole JC, Taylor R. A new test set for validating predictions of protein-ligand interaction. Proteins. 2002;49:457–71.
Verdonk ML, Cole JC, Hartshorn MJ, Murray CW, Taylor RD. Improved protein-ligand docking using GOLD. Proteins. 2003;52:609–23.
Annamala MK, Inampudi KK, Guruprasad L. Docking of phosphonate and trehalose analog inhibitors into M. tuberculosis mycolyltransferase Ag85C: Comparison of the two scoring fitness functions GoldScore and ChemScore, in the GOLD software. Bioinformation. 2007;1:339–50.
Baxter CA, Murray CW, Clark DE, Westhead DR, Eldridge MD. Flexible docking using Tabu search and an empirical estimate of binding affinity. Proteins. 1998;33:367–82.
Skretas G, Wood DW. Rapid detection of subtype-selective nuclear hormone receptor binding with bacterial genetic selection. Appl Environ Microbiol. 2005;71:8995–7.
Skretas G, Wood DW. A bacterial biosensor of endocrine modulators. J Mol Biol. 2005;349:464–74.
Skretas G, Meligova AK, Villalonga-Barber C, Mitsiou DJ, Alexis MN, Micha-Screttas M, et al. Engineered chimeric enzymes as tools for drug discovery: generating reliable bacterial screens for the detection, discovery, and assessment of estrogen receptor modulators. J Am Chem Soc. 2007;129:8443–57.
Meek PJ, Liu Z, Tian L, Wang CY, Welsh WJ, Zauhar RJ. Shape Signatures: speeding up computer aided drug discovery. Drug Discov Today. 2006;11:895–904.
Labrie F, Labrie C, Belanger A, Simard J, Gauthier S, Luu-The V, et al. EM-652 (SCH 57068), a third generation SERM acting as pure antiestrogen in the mammary gland and endometrium. J Steroid Biochem Mol Biol. 1999;69:51–84.
SPSS. Chicago, IL: SPSS; 2005.
Grimm LG, Yarnold PR. Reading and understanding more multivariate statistics. Washington, DC: American Psychological Association; 2000.
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The protein data bank. Nucleic Acids Res. 2000;28:235–42.
Shiau AK, Barstad D, Loria PM, Cheng L, Kushner PJ, Agard DA, et al. The structural basis of estrogen receptor/coactivator recognition and the antagonism of this interaction by tamoxifen. Cell. 1998;95:927–37.
SYBYL. St. Louis, MO: Tripos Inc; 2001.
Levai A, Bognár R. Oxazepines and thiazepines, III. Synthesis of 2,3-dihydro-2,4-diphenyl-1,5-benzothiazepines by the reaction of 2-aminothiophenol with chalcones substituted in ring A. Acta Chim Acad Sci Hung. 1977;92:415–9.
Sharma G, Raj K, Chakraborti AK. Fluoroboric acid adsorbed on silica-gel (HBF4-SiO2) as a new, highly efficient and reusable heterogeneous catalyst for thia-Michael addition to α, β-unsaturated carbonyl compounds. Tetrahedron Lett. 2008;49:4272–5.
Fang H, Tong W, Shi LM, Blair R, Perkins R, Branham W, et al. Structure-activity relationships for a large diverse set of natural, synthetic, and environmental estrogens. Chem Res Toxicol. 2001;14:280–94.
Wang CY, Ai N, Arora S, Erenrich E, Nagarajan K, Zauhar R, et al. Identification of previously unrecognized antiestrogenic chemicals using a novel virtual screening approach. Chem Res Toxicol. 2006;19:1595–601.
Ambrose Amin E, Welsh WJ. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a novel class of piperazine-based stromelysin-1 (MMP-3) inhibitors: applying a “divide and conquer” strategy. J Med Chem. 2001;44:3849–55.
ACKNOWLEDGMENT
This work was partially supported by NIH grant 1R21ES16630.
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Hartman, I., Gillies, A.R., Arora, S. et al. Application of Screening Methods, Shape Signatures and Engineered Biosensors in Early Drug Discovery Process. Pharm Res 26, 2247–2258 (2009). https://doi.org/10.1007/s11095-009-9941-z
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DOI: https://doi.org/10.1007/s11095-009-9941-z