title: Prediction of hERG potassium channel affinity by traditional and hologram qSAR methods.
abstract: Traditional and hologram QSAR (HQSAR) models were developed for the prediction of hERG potassium channel affinities. The models were validated on three different test sets including compounds with published patch-clamp IC(50) data and two subsets from the World Drug Index (compounds indicated to have ECG modifying adverse effect and drugs marked to be approved, respectively). Discriminant analysis performed on the full set of hERG data resulted in a traditional QSAR model that classified 83% of actives and 87% of inactives correctly. Analysis of our HQSAR model revealed it to be predictive in both IC(50) and discrimination studies.
authors.affiliation: Computer Assisted Drug Discovery, Gedeon Richter Ltd, PO Box 27, H-1475 Budapest, Hungary. gy.keseru@richter.hu
authors.forename: György M
authors.initials: GM
authors.lastname: Keserü
mesh_terms: D027682:Cation Transport Proteins / Q000737:chemistry*; D016208:Databases, Factual; D016002:Discriminant Analysis; D051638:Ether-A-Go-Go Potassium Channels; D006696:Holography; D016014:Linear Models; D026902:Potassium Channel Blockers / Q000494:pharmacology; D015221:Potassium Channels / Q000737:chemistry*; D024642:Potassium Channels, Voltage-Gated; D021281:Quantitative Structure-Activity Relationship
chemical_list: D027682:Cation Transport Proteins; D051638:Ether-A-Go-Go Potassium Channels; C092509:KCNH6 protein, human; D026902:Potassium Channel Blockers; D015221:Potassium Channels; D024642:Potassium Channels, Voltage-Gated