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  • Title: Prediction of hERG potassium channel affinity by the CODESSA approach.
    Author: Coi A, Massarelli I, Murgia L, Saraceno M, Calderone V, Bianucci AM.
    Journal: Bioorg Med Chem; 2006 May 01; 14(9):3153-9. PubMed ID: 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.
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