Classification models for hERG inhibitors by counter-propagation neural networks

Chemical Biology and Drug Design

Volumn 72, Issue 4, 2008, Pages 279-289

  Thai, Khac Minh ^a   Ecker, Gerhard F ^a  

^a UNIVERSITY OF VIENNA   (Austria)

Author keywords

Classification; Counter propagation; GH score; Human ether a go go related gene (hERG); Neural networks

Indexed keywords

POTASSIUM CHANNEL BLOCKING AGENT; POTASSIUM CHANNEL HERG;

ACCURACY; ANIMAL CELL; ARTICLE; ARTIFICIAL NEURAL NETWORK; DRUG CLASSIFICATION; HUMAN; HUMAN CELL; IC 50; MODEL; NONHUMAN; PARTIAL LEAST SQUARES REGRESSION; PERFORMANCE; PRIORITY JOURNAL;

ALGORITHMS; ANIMALS; CELL LINE; CERCOPITHECUS AETHIOPS; COMPUTER SIMULATION; CRICETINAE; CRICETULUS; ETHER-A-GO-GO POTASSIUM CHANNELS; HUMANS; MODELS, MOLECULAR; NEURAL NETWORKS (COMPUTER); POTASSIUM CHANNEL BLOCKERS; REGRESSION ANALYSIS;

EID: 52649109749     PISSN: 17470277     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1747-0285.2008.00705.x     Document Type: Article

References (50)

1. Sanguinetti M.C., Tristani-Firouzi M. (2006) hERG potassium channels and cardiac arrhythmia. Nature 440 : 463 469.
2. Hoffmann P., Warner B. (2006) Are hERG channel inhibition and QT interval prolongation all there is in drug-induced torsadogenesis? A review of emerging trends. J Pharmacol Toxicol Methods 53 : 87 105.
3. Witchel H.J. (2007) The hERG potassium channel as a therapeutic target. Expert Opin Ther Targets 11 : 321 336.
4. Pearlstein R., Vaz R., Rampe D. (2003) Understanding the structure-activity relationship of the human ether-a-go-go-related gene cardiac K+ channel. A model for bad behavior. J Med Chem 46 : 2017 2022.
5. Thai K.-M., Ecker G.F. (2007) Predictive models for hERG channel blockers: ligand-based and structure-based approaches. Curr Med Chem 14 : 3003 3026.
6. Ekins S. (2003) In silico approaches to predicting drug metabolism, toxicology and beyond. Biochem Soc Trans 31 : 611 614.
7. Vaz R.J., Li Y., Rampe D. (2005) Human ether-a-go-go related gene (HERG): a chemist's perspective. In : King F.D., Lawton G., editors. Progress in Medical Chemistry. Amsterdam : Elsevier p. 1 18.
8. Aronov A.M. (2008) Tuning out of hERG. Curr Opin Drug Discov Devel 11 : 128 135.
9. Recanatini M., Poluzzi E., Masetti M., Cavalli A., De Ponti F. (2005) QT prolongation through hERG K(+) channel blockade: current knowledge and strategies for the early prediction during drug development. Med Res Rev 25 : 133 166.
10. Aronov A.M. (2005) Predictive in silico modeling for hERG channel blockers. Drug Discov Today 10 : 149 155.
11. Aronov A.M. (2006) Common pharmacophores for uncharged human ether-a-go-go-related gene (hERG) blockers. J Med Chem 49 : 6917 6921.
12. Cavalli A., Poluzzi E., De Ponti F., Recanatini M. (2002) Toward a pharmacophore for drugs inducing the long QT syndrome: insights from a CoMFA study of HERG K(+) channel blockers. J Med Chem 45 : 3844 3853.
13. Choe H., Nah K.H., Lee S.N., Lee H.S., Lee H.S., Jo S.H., Leem C.H., et al 2006) A novel hypothesis for the binding mode of HERG channel blockers. Biochem Biophys Res Commun 344 : 72 78.
14. Farid R., Day T., Friesner R.A., Pearlstein R.A. (2006) New insights about HERG blockade obtained from protein modeling, potential energy mapping, and docking studies. Bioorg Med Chem 14 : 3160 3173.
15. Stansfeld P.J., Gedeck P., Gosling M., Cox B., Mitcheson J.S., Sutcliffe M.J. (2007) Drug block of the hERG potassium channel: insight from modeling. Proteins 68 : 568 580.
16. Johnson S.R., Yue H., Conder M.L., Shi H., Doweyko A.M., Lloyd J., Levesque P. (2007) Estimation of hERG inhibition of drug candidates using multivariate property and pharmacophore SAR. Bioorg Med Chem 15 : 6182 6192.
17. Ekins S., Crumb W.J., Sarazan R.D., Wikel J.H., Wrighton S.A. (2002) Three-dimensional quantitative structure-activity relationship for inhibition of human ether-a-go-go-related gene potassium channel. J Pharmacol Exp Ther 301 : 427 434.
18. Song M., Clark M. (2006) Development and evaluation of an in silico model for hERG binding. J Chem Inf Model 46 : 392 400.
19. Diller D.J., Hobbs D.W. (2007) Understanding hERG inhibition with QSAR models based on a one-dimensional molecular representation. J Comput Aided Mol Des 21 : 379 393.
20. Seierstad M., Agrafiotis D.K. (2006) A QSAR model of HERG binding using a large, diverse, and internally consistent training set. Chem Biol Drug Des 67 : 284 296.
21. Österberg F., Aqvist J. (2005) Exploring blocker binding to a homology model of the open hERG K+ channel using docking and molecular dynamics methods. FEBS Lett 579 : 2939 2944.
22. Rajamani R., Tounge B.A., Li J., Reynolds C.H. (2005) A two-state homology model of the hERG K+ channel: application to ligand binding. Bioorg Med Chem Lett 15 : 1737 1741.
23. Yoshida K., Niwa T. (2006) Quantitative structure-activity relationship studies on inhibition of HERG potassium channels. J Chem Inf Model 46 : 1371 1378.
24. Pearlstein R.A., Vaz R.J., Kang J., Chen X.L., Preobrazhenskaya M., Shchekotikhin A.E., Koroleu A.M., et al. (2003) Characterization of HERG potassium channel inhibition using CoMSiA 3D QSAR and homology modeling approaches. Bioorg Med Chem Lett 13 : 1829 1835.
25. Kramer C., Beck B., Kriegl J.M., Clark T. (2008) A composite model for hERG blockade. ChemMedChem 3 : 254 265.
26. Fioravanzo E., Cazzolla N., Durando L., Ferrari C., Mabilia M., Ombrato R., Parenti M.D 2005) General and independent approaches to predict HERG affinity values. Internet Electron J Mol Des 4 : 625 646.
27. Keserü G.M. (2003) Prediction of hERG potassium channel affinity by traditional and hologram QSAR methods. Bioorg Med Chem Lett 13 : 2773 2775.
28. Gavaghan C.L., Arnby C.H., Blomberg N., Strandlund G., Boyer S. (2007) Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data. J Comput Aided Mol Des 21 : 189 206.
29. Thai K.-M., Ecker G.F. (2008) A binary QSAR model for classification of hERG potassium channel blockers. Bioorg Med Chem 16 : 4107 4119.
30. Bains W., Basman A., White C. (2004) HERG binding specificity and binding site structure: evidence from a fragment-based evolutionary computing SAR study. Prog Biophys Mol Biol 86 : 205 233.
31. Dubus E., Ijjaali I., Petitet F., Michel A. (2006) In silico classification of hERG channel blockers: a knowledge-based strategy. ChemMedChem 1 : 622 630.
32. Gepp M.M., Hutter M.C. (2006) Determination of hERG channel blockers using a decision tree. Bioorg Med Chem 14 : 5325 5332.
33. O'Brien S.E., de Groot M.J. (2005) Greater than the sum of its parts: combining models for useful ADMET prediction. J Med Chem 48 : 1287 1291.
34. Sun H. (2006) An accurate and interpretable bayesian classification model for prediction of hERG liability. ChemMedChem 1 : 315 322.
35. Roche O., Trube G., Zuegge J., Pflimlin P., Alanine A., Schneider G. (2002) A virtual screening method for prediction of the HERG potassium channel liability of compound libraries. ChemBioChem 3 : 455 459.
36. Tobita M., Nishikawa T., Nagashima R. (2005) A discriminant model constructed by the support vector machine method for HERG potassium channel inhibitors. Bioorg Med Chem Lett 15 : 2886 2890.
37. Li Q., Jørgensen F.S., Oprea T., Brunak S., Taboureau O. (2008) hERG classification model based on a combination of support vector machine method and GRIND descriptors. Mol Pharm 5 : 117 127.
38. Ekins S., Balakin K.V., Savchuk N., Ivanenkov Y. (2006) Insights for human ether-a-go-go-related gene potassium channel inhibition using recursive partitioning and Kohonen and Sammon mapping techniques. J Med Chem 49 : 5059 5071.
39. Labute P. (2000) A widely applicable set of descriptors. J Mol Graph Model 18 : 464 477.
40. Ecker G.F., Schindler S.U., Zdrazil B., Chiba P. (2006) Predictive models for P-glycoprotein substrates based on VSA-descriptors. The 231st ACS National Meeting. Atlanta, GA, United States : MEDI 326.
41. Roncaglioni A., Novic M., Vracko M., Benfenati E. (2004) Classification of potential endocrine disrupters on the basis of molecular structure using a nonlinear modeling method. J Chem Inf Comput Sci 44 : 300 309.
42. Burkard U. (2003) Methods for data analysis. In : Gasteiger J., Engel T., editors. Chemoinformatics: A Textbook. Weinheim : Wiley-VCH p. 439 486.
43. Zupan J., Gasteiger J. (1999) Neural Networks in Chemistry and Drug Design, 2nd Edn. Weinheim : Wiley-VCH.
44. Vracko M. (2005) Kohonen artificial neural network and counter propagation neural network in molecular structure-toxicity studies. Curr Comput Aided Drug Des 1 : 73 78.
45. Guner O.F., Henry D.R., Pearlman R.S. (1992) Use of flexible queries for searching conformationally flexible molecules in databases of three-dimensional structures. J Chem Inf Model 32 : 101 109.
46. Demel M.A., Janecek A.G.K., Thai K.-M., Ecker G.F., Gansterer W.N. (2008) Predictive QSAR models for polyspecific drug targets: the importance of feature selection. Curr Comput Aided Drug Des 4 : 91 110.
47. Waring M.J., Johnstone C. (2007) A quantitative assessment of hERG liability as a function of lipophilicity. Bioorg Med Chem Lett 17 : 1759 1764.
48. Kubinyi H. (2006) Validation and predictivity of QSAR models. In : Sener E.A., Yalcin I., editors. QSAR & Molecular Modelling in Rational Design of Bioactive Molecules (Proceedings of the 15th European Symposium on QSAR & Molecular Modelling, Istanbul, Turkey, 2004). Ankara, Turkey : CADDD Society p. 30 33.
49. Paola G. (2007) Principles of QSAR models validation: internal and external. QSAR Comb Sci 26 : 694 701.
50. Aronov A.M., Goldman B.B. (2004) A model for identifying HERG K+ channel blockers. Bioorg Med Chem 12 : 2307 2315.