Prediction of hERG potassium channel affinity by the CODESSA approach

被引:47
作者
Coi, A
Massarelli, I
Murgia, L
Saraceno, M
Calderone, V
Bianucci, AM
机构
[1] Univ Pisa, Dipartimento Sci Farmaceut, I-56126 Pisa, Italy
[2] Univ Pisa, Dipartimento Chim & Chim Ind, I-56126 Pisa, Italy
[3] Univ Pisa, Dipartimento Psichiat Neurobiol Farmacol & Biotec, I-56126 Pisa, Italy
关键词
hERG; CODESSA; property prediction;
D O I
10.1016/j.bmc.2005.12.030
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The problem of predicting torsadogenic cardiotoxicity of drugs is afforded in this work. QSAR studies oil 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 oil 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. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3153 / 3159
页数:7
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