Predictive models for hERG potassium channel blockers.
We report here a general method for the prediction of hERG potassium channel blockers using computational models generated from correlation analyses of a large dataset and pharmacophore-based GRIND descriptors. These 3D-QSAR models are compared favorably with other traditional and chemometric based HQSAR methods.
Cianchetta
Giovanni
G
Sanofi-Aventis Pharmaceuticals, 1041 Route 202/206 N, Bridgewater, NJ 08807, USA.
Li
Yi
Y
Kang
Jiesheng
J
Rampe
David
D
Fravolini
Arnaldo
A
Cruciani
Gabriele
G
Vaz
Roy J
RJ
D000889:Anti-Arrhythmia Agents / Q000737:chemistry / Q000494:pharmacology; D001665:Binding Sites; D006801:Humans; D020128:Inhibitory Concentration 50; D007536:Isomerism; D008958:Models, Molecular; D026902:Potassium Channel Blockers / Q000737:chemistry* / Q000494:pharmacology; D024642:Potassium Channels, Voltage-Gated / Q000037:antagonists & inhibitors*; D021281:Quantitative Structure-Activity Relationship; D012984:Software
D000889:Anti-Arrhythmia Agents; D026902:Potassium Channel Blockers; D024642:Potassium Channels, Voltage-Gated