Experimentally validated hERG pharmacophore models as cardiotoxicity prediction tools

Journal of Chemical Information and Modeling

Volumn 54, Issue 10, 2014, Pages 2887-2901

  Kratz, Jadel M ^a,b   Schuster, Daniela ^b   Edtbauer, Michael ^b   Saxena, Priyanka ^c   Mair, Christina E ^b   Kirchebner, Julia ^b   Matuszczak, Barbara ^b   Baburin, Igor ^c   Hering, Steffen ^c   Rollinger, Judith M ^b  

^a FEDERAL UNIVERSITY OF SANTA CATARINA   (Brazil)

^b UNIVERSITY OF INNSBRUCK   (Austria)

^c UNIVERSITY OF VIENNA   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL LIBRARIES; ELECTROPHYSIOLOGY;

CHANNEL BLOCKERS; COMPOUND LIBRARIES; EXPERIMENTAL VALIDATIONS; PATCH CLAMP TECHNIQUE; PHARMACOPHORE MODELING; PHARMACOPHORE MODELS; PREDICTION TOOLS; VIRTUAL SCREENING;

PHARMACODYNAMICS;

CARDIOTONIC AGENT; ERG1 POTASSIUM CHANNEL; LIGAND; MOLECULAR LIBRARY; POTASSIUM CHANNEL BLOCKING AGENT; POTASSIUM CHANNEL HERG; PROTEIN BINDING; RECOMBINANT PROTEIN;

ANTAGONISTS AND INHIBITORS; BINDING SITE; CHEMISTRY; COMPUTER INTERFACE; CONFORMATION; DRUG DESIGN; DRUG EFFECTS; DRUG SCREENING; GENE EXPRESSION; GENETICS; HEK293 CELL LINE; HIGH THROUGHPUT SCREENING; HUMAN; MEMBRANE POTENTIAL; MOLECULAR DYNAMICS; MOLECULAR LIBRARY; PATCH CLAMP TECHNIQUE; PHARMACOLOGY; STRUCTURE ACTIVITY RELATION;

BINDING SITES; CARDIOTONIC AGENTS; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; ETHER-A-GO-GO POTASSIUM CHANNELS; GENE EXPRESSION; HEK293 CELLS; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; LIGANDS; MEMBRANE POTENTIALS; MOLECULAR CONFORMATION; MOLECULAR DYNAMICS SIMULATION; PATCH-CLAMP TECHNIQUES; POTASSIUM CHANNEL BLOCKERS; PROTEIN BINDING; RECOMBINANT PROTEINS; SMALL MOLECULE LIBRARIES; STRUCTURE-ACTIVITY RELATIONSHIP; USER-COMPUTER INTERFACE;

EID: 84908225434     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci5001955     Document Type: Article

References (74)

1. Yap, Y. G.; Camm, A. J. Drug induced QT prolongation and torsades de pointes Heart 2003, 89, 1363-1372
2. Sanguinetti, M. C.; Tristani-Firouzi, M. hERG potassium channels and cardiac arrhythmia Nature 2006, 440, 463-469
3. + channels: Structure, function, and clinical significance Physiol. Rev. 2012, 92, 1393-1478
4. Redfern, W. S.; Carlsson, L.; Davis, A. S.; Lynch, W. G.; MacKenzie, I.; Palethorpe, S.; Siegl, P. K.; Strang, I.; Sullivan, A. T.; Wallis, R.; Camm, A. J.; Hammond, T. G. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: Evidence for a provisional safety margin in drug development Cardiovasc. Res. 2003, 58, 32-45
5. Guidance on S7B Nonclinical Evaluation of the Potential for Delayed Ventricular Repolarization (QT Interval Prolongation) by Human Pharmaceuticals; International Conference on Harmonisation: Geneva, 2005; pp 1-9
6. Raschi, E.; Ceccarini, L.; De Ponti, F.; Recanatini, M. hERG-related drug toxicity and models for predicting hERG liability and QT prolongation Expert Opin. Drug Metab. Toxicol. 2009, 5, 1005-1021
7. Chi, K. R. Revolution dawning in cardiotoxicity testing Nat. Rev. Drug Discovery 2013, 12, 565-567
8. Dennis, A.; Wang, L.; Wan, X.; Ficker, E. hERG channel trafficking: Novel targets in drug-induced long QT syndrome Biochem. Soc. Trans. 2007, 35, 1060-1063
9. Durdagi, S.; Deshpande, S.; Duff, H. J.; Noskov, S. Y. Modeling of open, closed, and open-inactivated states of the hERG1 channel: Structural mechanisms of the state-dependent drug binding J. Chem. Inf. Model. 2012, 52, 2760-2774
10. Vilums, M.; Overman, J.; Klaasse, E.; Scheel, O.; Brussee, J.; Ijzerman, A. P. Understanding of molecular substructures that contribute to hERG K+ channel blockade: Synthesis and biological evaluation of E-4031 analogues ChemMedChem 2012, 7, 107-113
11. Lawrence, C. L.; Pollard, C. E.; Hammond, T. G.; Valentin, J. P. In vitro models of proarrhythmia Br. J. Pharmacol. 2008, 154, 1516-1522
12. + channel inhibition by combining 3D-QSAR pharmacophore and 2D-QSAR models J. Mol. Model. 2012, 18, 1023-1036
13. Su, B. H.; Shen, M. Y.; Esposito, E. X.; Hopfinger, A. J.; Tseng, Y. J. In silico binary classification QSAR models based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage J. Chem. Inf. Model. 2010, 50, 1304-1318
14. Polak, S.; Wis̈niowska, B.; Ahamadi, M.; Mendyk, A. Prediction of the hERG potassium channel inhibition potential with use of artificial neural networks Appl. Soft Comput. 2011, 11, 2611-2617
15. Ekins, S.; Crumb, W. J.; Sarazan, R. D.; Wikel, J. H.; Wrighton, S. A. Three-dimensional quantitative structure-activity relationship for inhibition of human ether-a-go-go-related gene potassium channel J. Pharmacol. Exp. Ther. 2002, 301, 427-434
16. Rayan, A.; Falah, M.; Raiyn, J.; Daadoosh, B.; Kadan, S.; Zaid, H.; Goldblum, A. Indexing molecules for their hERG liability Eur. J. Med. Chem. 2013, 65, 304-314
17. + Channel Blockers J. Med. Chem. 2002, 45, 3844-3853
18. Durdagi, S.; Duff, H. J.; Noskov, S. Y. Combined receptor and ligand-based approach to the universal pharmacophore model development for studies of drug blockade to the hERG1 pore domain J. Chem. Inf. Model. 2011, 51, 463-474
19. Johnson, S. R.; Yue, H.; Conder, M. L.; Shi, H.; Doweyko, A. M.; Lloyd, J.; Levesque, P. Estimation of hERG inhibition of drug candidates using multivariate property and pharmacophore SAR Bioorg. Med. Chem. 2007, 15, 6182-6192
20. Leong, M. K. A novel approach using pharmacophore ensemble/support vector machine (PhE/SVM) for prediction of hERG liability Chem. Res. Toxicol. 2007, 20, 217-226
21. Yamakawa, Y.; Furutani, K.; Inanobe, A.; Ohno, Y.; Kurachi, Y. Pharmacophore modeling for hERG channel facilitation Biochem. Biophys. Res. Commun. 2012, 418, 161-166
22. + channel pore and known ligands J. Mol. Graphics Modell. 2013, 46, 93-104
23. Wang, M.; Yang, X.-G.; Xue, Y. Identifying hERG potassium channel inhibitors by machine learning methods QSAR Comb. Sci. 2008, 27, 1028-1035
24. Wang, S.; Li, Y.; Wang, J.; Chen, L.; Zhang, L.; Yu, H.; Hou, T. ADMET evaluation in drug discovery. 12. Development of binary classification models for prediction of hERG potassium channel blockage Mol. Pharmaceutics 2012, 9, 996-1010
25. Zemzemi, N.; Bernabeu, M. O.; Saiz, J.; Cooper, J.; Pathmanathan, P.; Mirams, G. R.; Pitt-Francis, J.; Rodriguez, B. Computational assessment of drug-induced effects on the electrocardiogram: From ion channel to body surface potentials Br. J. Pharmacol. 2013, 168, 718-733
26. Wang, S.; Li, Y.; Xu, L.; Li, D.; Hou, T. Recent developments in computational prediction of hERG blockage Curr. Top. Med. Chem. 2013, 13, 1317-1326
27. Broccatelli, F.; Mannhold, R.; Moriconi, A.; Giuli, S.; Carosati, E. QSAR modeling and data mining link Torsades de Pointes risk to the interplay of extent of metabolism, active transport, and HERG liability Mol. Pharmaceutics 2012, 9, 2290-2301
28. Doddareddy, M. R.; Klaasse, E. C.; Shagufta; Ijzerman, A. P.; Bender, A. Prospective validation of a comprehensive in silico hERG model and its applications to commercial compound and drug databases ChemMedChem 2010, 5, 716-729
29. Beattie, K. A.; Luscombe, C.; Williams, G.; Munoz-Muriedas, J.; Gavaghan, D. J.; Cui, Y.; Mirams, G. R. Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge J. Pharmacol. Toxicol. Methods 2013, 68, 88-96
30. Czodrowski, P. hERG me out J. Chem. Inf. Model. 2013, 53, 2240-2251
31. Gavaghan, C. L.; Arnby, C. H.; Blomberg, N.; Strandlund, G.; Boyer, S. Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data J. Comput.-Aided Mol. Des. 2007, 21, 189-206
32. Ekins, S.; Mestres, J.; Testa, B. In silico pharmacology for drug discovery: Applications to targets and beyond Br. J. Pharmacol. 2007, 152, 21-37
33. Schuster, D. 3D pharmacophores as tools for activity profiling Drug Discovery Today: Technol. 2010, 7, e205-e211
34. Sanders, M. P.; Barbosa, A. J.; Zarzycka, B.; Nicolaes, G. A.; Klomp, J. P.; de Vlieg, J.; Del Rio, A. Comparative analysis of pharmacophore screening tools J. Chem. Inf. Model. 2012, 52, 1607-1620
35. Spitzer, G. M.; Heiss, M.; Mangold, M.; Markt, P.; Kirchmair, J.; Wolber, G.; Liedl, K. R. One concept, three implementations of 3D pharmacophore-based virtual screening: Distinct coverage of chemical search space J. Chem. Inf. Model. 2010, 50, 1241-1247
36. Du-Cuny, L.; Chen, L.; Zhang, S. A critical assessment of combined ligand- and structure-based approaches to HERG channel blocker modeling J. Chem. Inf. Model. 2011, 51, 2948-2960
37. Catalyst Software Package, version 4.7; Accelrys Software Inc.: San Diego, CA, 2003.
38. Schuster, D.; Waltenberger, B.; Kirchmair, J.; Distinto, S.; Markt, P.; Stuppner, H.; Rollinger, J. M.; Wolber, G. Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part I: Model generation, validation and applicability in ethnopharmacology Mol. Inf. 2010, 29, 75-86
39. Wolber, G.; Langer, T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters J. Chem. Inf. Model. 2005, 45, 160-169
40. + channels in human heart: Comparison with terfenadine under physiological conditions J. Pharmacol. Exp. Ther. 2000, 292, 261-264
41. + channels expressed in a mammalian cell line J. Pharmacol. Exp. Ther. 2000, 294, 339-346
42. Kim, K.-S.; Kim, E.-J. The phenothiazine drugs inhibit hERG potassium channels Drug Chem. Toxicol. 2005, 28, 303-313
43. Kuryshev, Y. A.; Brown, A. M.; Wang, L.; Benedict, C. R.; Rampe, D. Interactions of the 5-hydroxytryptamine 3 antagonist class of antiemetic drugs with human cardiac ion channels J. Pharmacol. Exp. Ther. 2000, 295, 614-620
44. Sanchez-Chapula, J. A.; Ferrer, T.; Navarro-Polanco, R. A.; Sanguinetti, M. C. Voltage-dependent profile of human Ether-a-go-go -related gene channel block is influenced by a single residue in the S6 transmembrane domain Mol. Pharmacol. 2003, 63, 1051-1058
45. Teschemacher, A. G.; Seward, E. P.; Hancox, J. C.; Witchel, H. J. Inhibition of the current of heterologously expressed HERG potassium channels by imipramine and amitriptyline Br. J. Pharmacol. 1999, 128, 479-485
46. Tie, H.; Walker, B. D.; Singleton, C. B.; Valenzuela, S. M.; Bursill, J. A.; Wyse, K. R.; Breit, S. N.; Campbell, T. J. Inhibition of HERG potassium channels by the antimalarial agent halofantrine Br. J. Pharmacol. 2000, 130, 1967-1975
47. Walker, B. D.; Valenzuela, S. M.; Singleton, C. B.; Tie, H.; Bursill, J. A.; Wyse, K. R.; Qiu, M. R.; Breit, S. N.; Campbell, T. J. Inhibition of hERG channels stably expressed in a mammalian cell line by the antianginal agent perhexiline maleate Br. J. Pharmacol. 1999, 127, 243-251
48. Zhang, S.; Rajamani, S.; Chen, Y.; Gong, Q.; Rong, Y.; Zhou, Z.; Ruoho, A.; January, C. T. Cocaine blocks HERG, but not KvLQT1+minK, potassium channels Mol. Pharmacol. 2001, 59, 1069-1076
49. Zhang, S.; Zhou, Z.; Gong, Q.; Makielski, J. C.; January, C. T. Mechanism of block and identification of the verapamil binding domain to HERG potassium channels Circ. Res. 1999, 84, 989-998
50. Aronov, A. M. Predictive in silico modeling for hERG channel blockers Drug Discovery Today 2005, 10, 149-155
51. de Bruin, M. L.; Pettersson, M.; Meyboon, R. H. B.; Hoes, A. W.; Leufkens, H. G. M. Anti-HERG activity and the risk of drug-induced arrhythmias and sudden death Eur. Heart J. 2005, 26, 590-597
52. Baburin, I.; Beyl, S.; Hering, S. Automated fast perfusion of Xenopus oocytes for drug screening Pflugers Arch. 2006, 453, 117-123
53. Milligan, C. J.; Li, J.; Sukumar, P.; Majeed, Y.; Dallas, M. L.; English, A.; Emery, P.; Porter, K. E.; Smith, A. M.; McFadzean, I.; Beccano-Kelly, D.; Bahnasi, Y.; Cheong, A.; Naylor, J.; Zeng, F.; Liu, X.; Gamper, N.; Jiang, L. H.; Pearson, H. A.; Peers, C.; Robertson, B.; Beech, D. J. Robotic multiwell planar patch-clamp for native and primary mammalian cells Nat. Protoc. 2009, 4, 244-255
54. Polonchuk, L. Toward a new gold standard for early safety: Automated temperature-controlled hERG test on the PatchLiner Front. Pharmacol. 2012, 3, 1-7
55. Jenks, C. W. Extraction studies of Tabernanthe iboga and Voacanga africana Nat. Prod. Lett. 2002, 16, 71-76
56. Koenig, X.; Kovar, M.; Rubi, L.; Mike, A. K.; Lukacs, P.; Gawali, V. S.; Todt, H.; Hilber, K.; Sandtner, W. Anti-addiction drug ibogaine inhibits voltage-gated ionic currents: A study to assess the drugs cardiac ion channel profile Toxicol. Appl. Pharmacol. 2013, 273, 259-268
57. Vuorinen, A.; Nashev, L. G.; Odermatt, A.; Rollinger, J. M.; Schuster, D. Pharmacophore model refinement for 11-hydroxysteroid dehydrogenase inhibitors: Search for modulators of intracellular glucocorticoid concentrations Mol. Inf. 2014, 33, 15-25
58. Klon, A. E. Machine learning algorithms for the prediction of hERG and CYP450 binding in drug development Exp. Opin. Drug Metab. Toxicol. 2010, 6, 821-833
59. Hawkins, P. C.; Nicholls, A. Conformer generation with OMEGA: Learning from the data set and the analysis of failures J. Chem. Inf. Model. 2012, 52, 2919-2936
60. Hawkins, P. C.; Skillman, A. G.; Warren, G. L.; Ellingson, B. A.; Stahl, M. T. Conformer generation with OMEGA: Algorithm and validation using high quality structures from the Protein Databank and Cambridge Structural Database J. Chem. Inf. Model. 2010, 50, 572-584
61. OMEGA, version 2.3.3; OpenEye Scientific Software: Santa Fe, NM, 2009-2013.
62. Gaulton, A.; Bellis, L. J.; Bento, A. P.; Chambers, J.; Davies, M.; Hersey, A.; Light, Y.; McGlinchey, S.; Michalovich, D.; Al-Lazikani, B.; Overington, J. P. ChEMBL: A large-scale bioactivity database for drug discovery Nucleic Acids Res. 2012, 40, D1100-D1107
63. Dunlop, J.; Bowlby, M.; Peri, R.; Vasilyev, D.; Arias, R. High-throughput electrophysiology: An emerging paradigm for ion-channel screening and physiology Nat. Rev. Drug Discovery 2008, 7, 358-368
64. 1-antihistamines for the treatment of insomnia Bioorg. Med. Chem. Lett. 2009, 19, 4380-4384
65. Lin, H.; Yamashita, D. S.; Xie, R.; Zeng, J.; Wang, W.; Leber, J.; Safonov, I. G.; Verma, S.; Li, M.; Lafrance, L.; Venslavsky, J.; Takata, D.; Luengo, J. I.; Kahana, J. A.; Zhang, S.; Robell, K. A.; Levy, D.; Kumar, R.; Choudhry, A. E.; Schaber, M.; Lai, Z.; Brown, B. S.; Donovan, B. T.; Minthorn, E. A.; Brown, K. K.; Heerding, D. A. Tetrasubstituted pyridines as potent and selective AKT inhibitors: Reduced CYP450 and hERG inhibition of aminopyridines Bioorg. Med. Chem. Lett. 2010, 20, 684-688
66. 1-antihistamines for the treatment of insomnia Bioorg. Med. Chem. Lett. 2010, 20, 2316-2320
67. Webb, R. L.; Schiering, N.; Sedrani, R.; Maibaum, J. Direct renin inhibitors as a new therapy for hypertension J. Med. Chem. 2010, 53, 7490-7520
68. Park, S. J.; Buschmann, H.; Bolm, C. Bioactive sulfoximines: Syntheses and properties of Vioxx analogs Bioorg. Med. Chem. Lett. 2011, 21, 4888-4890
69. Schuster, D.; Laggner, C.; Steindl, T. M.; Palusczak, A.; Hartmann, R. W.; Langer, T. Pharmacophore modeling and in silico screening for new P450 19 (aromatase) inhibitors J. Chem. Inf. Model. 2006, 46, 1301-1311
70. Wolber, G.; Dornhofer, A. A.; Langer, T. Efficient overlay of small organic molecules using 3D pharmacophores J. Comput.-Aided Mol. Des. 2006, 20, 773-788
71. Seidel, T.; Ibis, G.; Bendix, F.; Wolber, G. Strategies for 3D pharmacophore-based virtual screening Drug Discovery Today: Technol. 2010, 7, e221-e228
72. Li, H.; Sutter, J.; Hoffmann, R. HypoGen: An Automated System for Generating 3D Predictive Pharmacophore Models. In Pharmacophore Perception, Development, and Use in Drug Design; Güner, O. F., Ed.; International University Line: La Jolla, CA, 2000; pp 172-189.
73. Stork, D.; Timin, E. N.; Berjukow, S.; Huber, C.; Hohaus, A.; Auer, M.; Hering, S. State dependent dissociation of HERG channel inhibitors Br. J. Pharmacol. 2007, 151, 1368-1376
74. Windisch, A.; Timin, E.; Schwarz, T.; Stork-Riedler, D.; Erker, T.; Ecker, G.; Hering, S. Trapping and dissociation of propafenone derivatives in HERG channels Br. J. Pharmacol. 2011, 162, 1542-1552-1552