Prediction of hERG potassium channel affinity by traditional and hologram qSAR methods

Bioorg Med Chem Lett. 2003 Aug 18;13(16):2773-5. doi: 10.1016/s0960-894x(03)00492-x.


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.

Publication types

  • Comparative Study

MeSH terms

  • Cation Transport Proteins / chemistry*
  • Databases, Factual
  • Discriminant Analysis
  • Ether-A-Go-Go Potassium Channels
  • Holography
  • Linear Models
  • Potassium Channel Blockers / pharmacology
  • Potassium Channels / chemistry*
  • Potassium Channels, Voltage-Gated*
  • Quantitative Structure-Activity Relationship


  • Cation Transport Proteins
  • Ether-A-Go-Go Potassium Channels
  • KCNH6 protein, human
  • Potassium Channel Blockers
  • Potassium Channels
  • Potassium Channels, Voltage-Gated