2006
DOI: 10.1002/cmdc.200500099
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In Silico Classification of hERG Channel Blockers: a Knowledge‐Based Strategy

Abstract: The blockage of the hERG potassium channel by a wide number of diverse compounds has become a major pharmacological safety concern as it can lead to sudden cardiac death. In silico models can be potent tools to screen out potential hERG blockers as early as possible during the drug-discovery process. In this study, predictive models developed using the recursive partitioning method and created using diverse datasets from 203 molecules tested on the hERG channel are described. The first model was built with hER… Show more

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Cited by 49 publications
(73 citation statements)
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References 24 publications
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“…Recent studies have involved homology modeling, docking studies, classical or hologram 2D-QSAR (two-dimensional quantitative structure-activity relationships) and 3D-QSAR (Aptula and Cronon, 2004;Aronov, 2005;Cavalli et al, 2002;Cianchetta et al, 2005;Coi et al, 2006;Diller and Hobbs, 2007;Du et al, 2004Du et al, , 2007Ekins et al, 2002Ekins et al, , 2006Fioravanzo et al, 2004;Guth, 2007;Johnson et al, 2007;Keserü, 2003;Pearlstein et al, 2003;Seierstad and Agrafiotis, 2006;Thai and Ecker, 2008) or classification methods (Aronov and Goldman, 2004;Aronov, 2005;Dubus et al, 2006;Gepp and Hutter, 2006;Guth, 2007;Leong, 2007;Li et al, 2008;Song and Clark, 2006;Sun, 2006;Tobita et al, 2005;Waring and Johnstone, 2007). The data quality and consistency is the crucial issue for the in silico models' quality and performance.…”
Section: Electrophysiological Assaysmentioning
confidence: 98%
“…Recent studies have involved homology modeling, docking studies, classical or hologram 2D-QSAR (two-dimensional quantitative structure-activity relationships) and 3D-QSAR (Aptula and Cronon, 2004;Aronov, 2005;Cavalli et al, 2002;Cianchetta et al, 2005;Coi et al, 2006;Diller and Hobbs, 2007;Du et al, 2004Du et al, , 2007Ekins et al, 2002Ekins et al, , 2006Fioravanzo et al, 2004;Guth, 2007;Johnson et al, 2007;Keserü, 2003;Pearlstein et al, 2003;Seierstad and Agrafiotis, 2006;Thai and Ecker, 2008) or classification methods (Aronov and Goldman, 2004;Aronov, 2005;Dubus et al, 2006;Gepp and Hutter, 2006;Guth, 2007;Leong, 2007;Li et al, 2008;Song and Clark, 2006;Sun, 2006;Tobita et al, 2005;Waring and Johnstone, 2007). The data quality and consistency is the crucial issue for the in silico models' quality and performance.…”
Section: Electrophysiological Assaysmentioning
confidence: 98%
“…Whilst some models [13][14][15][16][17] have been developed to discriminate between potent inhibitors (IC 50 < 1 mM) and 'non-inhibitors' (IC 50 > X mM, where X ! 10), these would be of limited utility in drug discovery, where many compound series exhibit 'moderate' inhibition -with IC 50 values in the range of 1-10 mM.…”
Section: Binary Classifiersmentioning
confidence: 99%
“…The ligand-based approach has been adopted to extract the features of hERG blockers in terms of inhibition of hERG current [9][10][11][12][13]. These methods include traditional two-dimensional (2D)-quantitative structure activity relationships (QSAR) [11,[14][15][16], 3D-QSAR [17][18][19][20][21][22], and classifi cation [23][24][25][26] methods. These methods extract chemical properties such as steric, hydrophobic, and electronic properties from the compounds.…”
Section: Ligand-based Prediction System For the Blockade Of Herg Currentmentioning
confidence: 99%
“…Or a combinatorial method with a classification [23,24] based on a decision tree algorithm, which divides blockers into a hierarchy of homogeneous subgroups using the descriptors, can be used. By fi tting the compounds to subgroup-specifi c pharmacophore models, the predicted activities of compounds have been reported to become closer to their actual activities [9,16,46].…”
Section: Issues and Resolutionsmentioning
confidence: 99%