Channelpedia

PubMed 16426850


Referenced in: none

Automatically associated channels: Kv11.1



Title: Prediction of hERG potassium channel affinity by the CODESSA approach.

Authors: Alessio Coi, Ilaria Massarelli, Laura Murgia, Marilena Saraceno, Vincenzo Calderone, Anna Maria Bianucci

Journal, date & volume: Bioorg. Med. Chem., 2006 May 1 , 14, 3153-9

PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/16426850


Abstract
The problem of predicting torsadogenic cardiotoxicity of drugs is afforded in this work. QSAR studies on a series of molecules, acting as hERG K+ channel blockers, were carried out for this purpose by using the CODESSA program. Molecules belonging to the analyzed dataset are characterized by different therapeutic targets and by high molecular diversity. The predictive power of the obtained models was estimated by means of rigorous validation criteria implying the use of highly diagnostic statistical parameters on the test set, other than the training set. Validation results obtained for a blind set, disjoined from the whole dataset initially considered, confirmed the predictive potency of the models proposed here, so suggesting that they are worth to be considered as a valuable tool for practical applications in predicting the blockade of hERG K+ channels.