Prediction of hERG potassium channel affinity by the CODESSA approach.
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.
Coi
Alessio
A
Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.
Massarelli
Ilaria
I
Murgia
Laura
L
Saraceno
Marilena
M
Calderone
Vincenzo
V
Bianucci
Anna Maria
AM
D002460:Cell Line; D051638:Ether-A-Go-Go Potassium Channels / Q000037:antagonists & inhibitors* / Q000378:metabolism*; D006801:Humans; D020128:Inhibitory Concentration 50; D015394:Molecular Structure; D026902:Potassium Channel Blockers / Q000737:chemistry / Q000494:pharmacology; D021281:Quantitative Structure-Activity Relationship
D051638:Ether-A-Go-Go Potassium Channels; D026902:Potassium Channel Blockers