Toluidinesulfonamide hypoxia-induced factor 1 inhibitors: Alleviating drug-drug interactions through use of pubchem data and comparative molecular field analysis guided synthesis

Journal of Medicinal Chemistry

Volumn 54, Issue 11, 2011, Pages 3982-3986

  Wendt, Bernd ^a   Mülbaier, Marcel ^a   Wawro, Sabine ^a   Schultes, Christoph ^a,b   Alonso, Jorge ^a   Janssen, Bernd ^a   Lewis, Joe ^a  

^a Elara Pharmaceuticals GmbH   (Germany)

^b Merck Serono GmbH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CYTOCHROME P450 2C9; HYPOXIA INDUCIBLE FACTOR 1; PROTEIN INHIBITOR; SULFONAMIDE; TOLUIDINE DERIVATIVE;

ARTICLE; COMPARATIVE MOLECULAR FIELD ANALYSIS; DATA ANALYSIS; DATA BASE; DRUG SELECTIVITY; HUMAN; STRUCTURE ACTIVITY RELATION;

ARYL HYDROCARBON HYDROXYLASES; DATABASES, FACTUAL; DRUG DESIGN; DRUG INTERACTIONS; HUMANS; HYPOXIA-INDUCIBLE FACTOR 1; LIGANDS; MOLECULAR STRUCTURE; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SULFONAMIDES; TOLUIDINES;

EID: 79958178893     PISSN: 00222623     EISSN: 15204804     Source Type: Journal    
DOI: 10.1021/jm200272h     Document Type: Article

References (30)

1. Semenza, G. L. HIF-1 and tumor progression: Pathophysiology and therapeutics. Trends Mol. Med. 2002, 8, S62-S67. (Pubitemid 34297081)
2. Vaupel, P.; Mayer, A. Hypoxia in cancer: Significance and impact on clinical outcome. Cancer Metastasis Rev. 2007, 26, 225-339.
3. Semenza, G. L. Evaluation of HIF-1 inhibitors as anticancer agents. Drug Discovery Today 2007, 12, 853-859. (Pubitemid 47554628)
4. Rapisarda, A.; Uranchimeg, B.; Scudiero, D. A.; Selby, M.; Sausville, E. A.; Shoemaker, R. H.; Melillo, G. Identification of small molecule inhibitors of hypoxia-inducible factor 1 transcriptional activation pathway. Cancer Res. 2002, 62, 4316-4324. (Pubitemid 34827288)
5. Kung, A. L.; Zabludoff, S. D.; France, D. S.; Freedman, S. J.; Tanner, E. A.; Vieira, A.; Cornell-Kennon, S.; Lee, J.; Wang, B.; Wang, J.; Memmert, K.; Naegeli, H. U.; Petersen, F.; Eck, M. J.; Bair, K. W.; Wood, A. W.; Livingston, D. M. Small molecule blockade of transcriptional coactivation of the hypoxia-inducible factor pathway. Cancer Cell 2004, 6, 33-43. (Pubitemid 38903160)
6. Welsh, S.; Williams, R.; Kirkpatrick, L.; Paine-Murrieta, G.; Powis, G. Antitumor activity and pharmacodynamic properties of PX- 478, an inhibitor of hypoxia-inducible factor-1alpha. Mol. Cancer Ther. 2004, 3, 233-244. (Pubitemid 39193698)
7. Chau, N. M.; Rogers, P.; Aherne, W.; Carroll, V.; Collins, I.; McDonald, E.; Workman, P.; Ashcroft, M. Identification of novel small molecule inhibitors of hypoxia-inducible factor-1 that differentially block hypoxia-inducible factor-1 activity and hypoxia-inducible factor-1alpha induction in response to hypoxic stress and growth factors. Cancer Res. 2005, 65, 4918-4928. (Pubitemid 40740832)
8. Greenberger, L. M.; Horak, I. D.; Filpula, D.; Sapra, P.; Westergaard, M.; Frydenlund, H. F.; Albaek, C.; Schrøder, H; Ørum, H. A RNA antagonist of hypoxia-inducible factor-1alpha, EZN-2968, inhibits tumor cell growth. Mol. Cancer Ther. 2008, 7, 3598-3608.
9. Miners, J. O.; Birkett, D. J. Cytochrome P4502C9: An enzyme of major importance in human drug metabolism. Br. J. Clin. Pharmacol. 1998, 45, 525-538. (Pubitemid 28270907)
10. Rettie, A. E.; Jones, J. P. Clinical and toxicological relevance of CYP2C9: Drug-drug interactions and pharmacogenetics. Annu. Rev. Pharmacol. Toxicol. 2005, 45, 477-494. (Pubitemid 40267790)
11. Payne, V. A.; Chang, Y. T.; Loew, G. H. Homology modeling and substrate binding study of human CYP2C9 enzyme. Proteins 1999, 37, 176-190. (Pubitemid 29503000)
12. De Groot, M. J.; Alex, A. A.; Jones, B. C. Development of a combined protein and pharmacophore model for cytochrome P450 2C9. J. Med. Chem. 2002, 45, 1983-1993. (Pubitemid 34477712)
13. Williams, P. A.; Cosme, J.; Ward, A.; Angove, H. C.; Matak- Vinkovic, D.; Jhoti, H. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature 2003, 424, 464-468. (Pubitemid 36917499)
14. Wester, M. R.; Yano, J. K.; Schoch, G. A.; Griffin, K. J.; Stout, C. D.; Johnson, E. F. Crystal structure of p4502c9 with flurbiprofen bound. J. Biol. Chem. 2004, 279, 35630-35637.
15. Afzelius, L.; Zamora, I.; Masimirembwa, C. M.; Karlén, A.; Andersson, T. B.; Mecucci, S.; Baroni, M.; Cruciani, G. Conformerand alignment-independent model for predicting structurally diverse competitive CYP2C9 inhibitors. J. Med. Chem. 2004, 47, 907-914. (Pubitemid 38176793)
16. Sun, H.; Scott, D. O. Structure-based drug metabolism predictions for drug design. Chem. Biol. Drug Des. 2010, 75, 3-17.
17. Sykes, M. J.; McKinnon, R. A.; Miners, J. O. Prediction of metabolism by cytochrome P450 2C9: Alignment and docking studies of a validated database of substrates. J. Med. Chem. 2008, 28, 780-791. (Pubitemid 351304687)
18. Jones, B. C.; Hawksworth, G.; Horne, V. A.; Newlands, A.; Morsman, J.; Tute, M. S.; Smith, D. A. Putative active site template model for cytochrome P4502C9 (tolbutamide hydroxylase). Drug Metab. Dispos. 1996, 24, 260-266. (Pubitemid 26063913)
19. Ekins, S.; Bravi, G.; Binkley, S.; Gillespie, J. S.; Ring, B. J.; Wikel, J. H.; Wrighton, S. A. Three- and four-dimensional-quantitative structure activity relationship (3D/4D-QSAR) analyses of CYP2C9 inhibitors. Drug Metab. Dispos. 2000, 28, 994-1002. (Pubitemid 30612621)
20. Rao, S.; Aoyama, R.; Schrag, M.; Trager, W. F.; Rettie, A.; Jones, J. P. A refined 3-dimensional QSAR of cytochrome P450 2C9: Computational predictions of drug interactions. J. Med. Chem. 2000, 43, 2789-2796. (Pubitemid 30599636)
21. PubChem Database. http://www.pubchem.org (accessed Oct 30, 2007).
22. Heritage, T. W.; Lowis, D. R. Molecular Hologram QSAR. In Rational Drug Design: Novel Methodology and Practical Applications; American Chemical Society: Washington, DC, 1999; pp 212-225. (Pubitemid 129547002)
23. Wendt, B.; Cramer, R. D. Quantitative series enrichment analysis (QSEA): A novel procedure for 3D-QSAR analysis. J. Comput.- Aided Mol. Des. 2008, 22, 541-551.
24. Wendt, B.; Uhrig, U.; Bös, F. Capturing structure- activityrelationships from chemogenomic spaces. J. Chem. Inf. Mod 2011, 51, 843-851.
25. Cramer, R. D. Topomer CoMFA: A design methodology for rapid lead optimization. J. Med. Chem. 2003, 46, 374-388. (Pubitemid 36139790)
26. 2 values above 0.2 between training set sizes of 85-95 compounds (see Supporting Information p S10). No model was chosen from this plateau because of insufficient structural variation within the training set.
27. Agarwal, A.; Pearson, P. P.; Taylor, E. W.; Li, H. B.; Dahlgren, T.; Herslöf, M.; Yang, Y.; Lambert, G.; Nelson, D. L.; Regan, J. W.; Martin, A. R. Three-dimensional quantitative structure-activity relationships of 5-HT receptor binding data for tetrahydropyridinylindole derivatives: A comparison of the Hansch and CoMFA methods. J. Med. Chem. 1993, 36, 4006-4014. (Pubitemid 24024672)
28. Doweyko, A. M. 3D-QSAR illusions. J. Comput.-Aided Mol. Des. 2004, 18, 587-596.
29. Golbraikh, A.; Tropsha, A. Beware of q2!. J. Mol. Graphics Modell. 2002, 20, 269-276. (Pubitemid 34017544)
30. Methoxy substituents represent potentially labile groups; however, in vivo studies later showed that introduction of the 4-methoxy group did not result in a metabolic liability for this series.