Discovery of estrogen receptor modulators: A review of virtual screening and SAR efforts

Expert Opinion on Drug Discovery

Volumn 5, Issue 1, 2010, Pages 21-31

  Xu, Xue ^a   Yang, Wei ^a   Li, Yan ^b   Wang, Yonghua ^a,b  

^a NORTHWEST A F UNIVERSITY   (China)

^b DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Drug discovery; Estrogen receptor modulator; SAR; Selectivity; Virtual screening

Indexed keywords

4 PROPYL 1,3,5 TRIPHENYLPYRAZOLE; BENZOXEPIN DERIVATIVE; ESTRADIOL; PYRAZOLE DERIVATIVE; RALOXIFENE; SELECTIVE ESTROGEN RECEPTOR MODULATOR; UNCLASSIFIED DRUG;

BIOLOGICAL ACTIVITY; CHEMICAL STRUCTURE; COMPUTER MODEL; HUMAN; MEDICAL INFORMATION; NONHUMAN; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RECEPTOR BINDING; REVIEW; SCREENING; STRUCTURE ACTIVITY RELATION; TOXICITY;

EID: 73649116395     PISSN: 17460441     EISSN: None     Source Type: Journal    
DOI: 10.1517/17460440903490395     Document Type: Review

References (54)

1. Osborne CK. Steroid hormone receptors in breast cancer management. Breast Cancer Res Treat 1998;51:227-238
2. Fuqua SA, Fitzgerald SD, Chamness GC, et al. Variant human breast tumor estrogen receptor with constitutive transcriptional activity. Cancer Res 1991;51:105-109
3. Keating NL, Cleary PD, Rossi AS, et al. Use of hormone replacement therapy by postmenopausal women in the United States. Ann Intern Med 1999;130:545-553
4. Ascenzi P, Bocedi A, Marino M. Structure-function relationship of estrogen receptor alpha and beta: Impact on human health. Mol Aspects Med 2006;27:299-402
5. Pike ACW, Brzozowski AM, Hubbard RE, 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;18:4608-4618
6. Plouffe L. Selective estrogen receptor modulators (SERMs) in clinical practice. J Soc Gynecol Investig 2000;7(1):38-46
7. Payre B, de Medina P, Mhamdi L, et al. Microsomal antiestrogen-binding site ligands induce growth control and differentiation of human breast cancer cells through the modulation of cholesterol metabolism. Mol Cancer Ther 2008;7:3707-3718
8. O'Neill K, Chen S, Brinton RD. Impact of the selective estrogen receptor modulator, raloxifene, on neuronal survival and outgrowth following toxic insults associated with aging and Alzheimer's disease. Exp Neurol 2004;185(1):63-80 (Pubitemid 38010279)
9. Lai KM, Scrimshaw MD, Lester JN. The effects of natural and synthetic steroid estrogens in relation to their environmental occurance. Crit Rev Toxicol 2002;32(2):113-132
10. Lyne PD. Structure-based virtual screening: an overview. DDT 2002;7(20):1047-1055
11. Cronin MTD, Jaworska JS, Walker JD, et al. Use of quantitative structure-activity relationships in international decision-making frameworks to predict health effects of chemical substances. Environ Health Perspect 2003;111:1376-1390
12. Xu H, Agrafiotis DK. Retrospect and prospect of virtual screening in drug discovery. Curr Top Med Chem 2002;2:1305-1320
13. Schmieder PK, Ankley G, Mekenyan O, et al. Quantitative structure-activity relationship models for prediction of estrogen receptor binding affinity of structurally diverse chemicals. Environ Toxicol Chem 2003;22(8):1844-1854
14. Hu JY, Aizawa T. Quantitative structure- activity relationships for estrogen receptor binding affinity of phenolic chemicals. Water Res 2003;37:1213-1222
15. Ghafourian T, Cronin MTD. The impact of variable selection on the modeling of oestrogenicity. SAR QSAR Environ Res 2005;16 (1-2):171-190
16. Liu H, Papa E, Gramatica P. Evaluation and QSAR modeling on multiple endpoints of estrogen activity based on different bioassays. Chemosphere 2008;70:1889-1897
17. Kurunczi L, Seclaman E, Oprea TI, et al. A PLS variant of the minimal topologic difference method. III. Mapping interactions between estradiol derivatives and the alpha estrogenic receptor. J Chem Inf Model 2005;45:1275-1281
18. Blower PE, Cross KP, Fligner MA, et al. Systematic analysis of large screening sets in drug discovery. Curr Drug Discov Technol 2004;1(1):37-47
19. Tong W, Hong H, Fang H, et al. Decision forest: combining the predictions of multiple independent decision tree models. J Chem Inf Comput Sci 2003;43:525-531
20. Tong W, Xie Q, Hong H, et al. Assessment of prediction confidence and domain extrapolation of two structure-activity relationship models for predicting estrogen receptor binding activity. Environ Health 2004;112(12):1249-1254
21. Hong H, Tong W, Xie Q, et al. An in silico ensemble method for lead discovery: decision forest. SAR QSAR Environ Res 2005;16(4):339-347
22. Asikainen A, Kolehmainen M, Ruuskanen J, Tuppurainen K. Structure-based classification of active and inactive estrogenic compounds by decision tree, LVQ and kNN methods. Chemosphere 2006;62(4):658-673
23. Asikainen AH, Ruuskanen J, Tuppurainen KA. 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 2004;38:6724-6729
24. Zupan J, Novič M, Gasteiger J. Neural networks with counter-propagation learning strategy used for modeling. Chemom Intell Lab Syst 2002;27(2):175-187
25. Roncaglioni A, Novič M, Vračko M, Benfenati E. Classification of potential endocrine disrupters on the basis of molecular structure using a nonlinear modeling method. J Chem Inf Comput Sci 2004;44:300-309
26. Marini F, Roncaglioni A, Novič M. Variable selection and interpretation in structure-affinity correlation modeling of estrogen receptor binders. J Chem Inf Model 2005;45:1507-1519
27. Specht DF. A general regression neural network. IEEE Trans Neural 2002;2(6):568-576
28. Agatonovic-Kustrin S, Turnerb JV, Glass BD. Molecular structural characteristics as determinants of estrogen receptor selectivity. J Pharm Biomed Anal 2008;48:369-375
29. Nilsson S, Koehler KF. Oestrogen receptors and selective oestrogen receptor modulators: molecular and cellular pharmacology. Basic Clin Pharmacol Toxicol 2005;96(1):15-25
30. Saji S, Hirose M, Toi M. Clinical significance of estrogen receptor beta in breast cancer. Cancer Chemother Pharmacol 2005;56(1):21-26
31. Wang Y, Li Y, Ding J, et al. Prediction of binding affinity for estrogen receptoralpha modulators using statistical learning approaches. Mol Divers 2008;12:93-102
32. Li H, Ung CY, Yap CW, et al. Prediction of estrogen receptor agonists and characterization of associated molecular descriptors by statistical learning methods. J Mol Graph Model 2006;25(3):313-323
33. Salum LB, Polikarpov I, Andricopulo AD. Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies. J Mol Graph Model 2007;26(2):434-442
34. Vedani A, Dobler M, Lill MA. Combining protein modeling and 6D-QSAR. Simulating the binding of structurally diverse ligands to the estrogen receptor. J Med Chem 2005;48:3700-3703
35. Klopman G, Chakravarti SK. Structure- activity relationship study of a diverse set of estrogen receptor ligands (I) using MultiCASE expert system. Chemosphere 2003;51:445-459
36. Cunningham AR, Cunningham SL, Rosenkranz HS. Structure-activity approach to the identification of environmental estrogens: the MCASE approach. SAR QSAR Environ Res 2004;15(1):55-67
37. Cramer RD, Patterson DE, Bunce JD. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J AM Chem Soc 1988;110:5959-5967
38. Kubinyi H. QSAR and 3D QSAR in drug design part 1: methodology. Drug Discov Today 1997;2(11):457-467
39. Cunha da EFF, Martins RCA, Albuquerque MG, Alencastro de RB. LIV-3D-QSAR model for estrogen receptor ligands. J Mol Model 2004;10:297-304
40. Demyttenaere-Kovatcheva A, Cronin MTD, Benfenati E, et al. Identification of the structural requirements of the receptor-binding affinity of diphenolic azoles to estrogen receptors alpha and beta by three-dimensional quantitative structure activity relationship and structure activity relationship analysis. J Med Chem 2005;48:7628-7636
41. Coleman KP, Toscano WA, Wiese TE. QSAR models of the in vitro estrogen activity of bisphenol analogs. J Chem Inf Comput Sci 2003;22(1):78-88
42. Waller CL. A comparative QSAR study using CoMFA, HQSAR, and FRED/ SKEYS paradigms for estrogen receptor binding affinities of structurally diverse compounds. J Chem Inf Comput Sci 2004;44(2):758-765
43. Korhonen SP, Tuppurainen K, Laatikainen R, Perakyla M. Comparing the performance of FLUFF-BALL to SEAL-CoMFA with a large diverse estrogen data set: from relevant superpositions to solid predictions. J Chem Inf Model 2005;45:1874-1883
44. Asikainen A, Ruuskanen J, Tuppurainen K. Spectroscopic QSAR methods and self-organizing molecular field analysis for relating molecular structure and estrogenic activity. J Chem Inf Comput Sci 2003;43:1974-1981
45. Salum LB, Polikarpov I, Andricopulo AD. Structure-based approach for the study of estrogen receptor binding af?nity and subtype selectivity. J Chem Inf Model 2008;48(11):2243-2253
46. Salum LB, Polikarpov I, Andricopulo AD. Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies. J Mol Graph Model 2007;26(2):434-442
47. Mukherjee S, Nagar S, Mullick S, et al. Pharmacophore mapping of selective binding affinity of estrogen modulators through classical and space modeling approaches: exploration of bridged-cyclic compounds with diarylethylene linkage. J Chem Inf Model 2007;47:475-487
48. Yang JM, Shen TW. A pharmacophore-based evolutionary approach for screening selective estrogen receptor modulators. Proteins 2005;59:205-220
49. Kekenes-Huskey PM, Muegge I, Rauch von M, et al. A molecular docking study of estrogenically active compounds with 1,2-diarylethane and 1,2-diarylethene pharmacophores. Bioorg Med Chem 2004;12(24):6527-6537
50. Barrett I, Meegan MJ, Hughes RB, et al. Synthesis, biological evaluation, structural-activity relationship, and docking study for a series of benzoxepin-derived estrogen receptor modulators. Bioorg Med Chem 2008;16:9554-9573
51. Wolohan P, Reichert DE. CoMFA and docking study of novel estrogen receptor subtype selective ligands. J Comput Aided Mol Des 2003;17:313-328
52. Dai SY, Burris TP, Dodge JA, et al. Unique ligand binding patterns between estrogen receptor alpha and beta revealed by hydrogen-deuterium exchange. Biochemistry 2009;48(40):9668-9676
53. Karnik PS, Kulkarni S, Liu XP, et al. Estrogen receptor mutations in tamoxifen-resistant breast cancer. Cancer Res 1994;54:349-353
54. Butina D, Segall MD, Frankcombe K. Predicting ADME properties in silico: methods and models. DDT 2002;7(11):583-588