Abstract
The development of a novel comprehensive approach for the prediction of hERG activity is herein presented. Software Phase has been used to derive a 3D-QSAR model, employing as alignment rule a common pharmacophore built on a subset of 22 highly active compounds (threshold Ki: 50 nM) against hERG K+ channel. Five features comprised the pharmacophore: two aromatic rings (R1 and R2), one hydrogen-bond acceptor (A), one hydrophobic site (H), and one positive ionizable function (P). The sequential 3D-QSAR model developed with a set of 421 compounds (randomly divided in training and test set) yielded a test set (Q2) = 0.802 and proved to be predictive with respect to an external test set of 309 compounds that were not used to generate the model ( = 0.860). Furthermore, the model was submitted to an in silico validation for assessing the reliability of the approach, by applying a decoys set, evaluating the Güner and Henry score (GH) and the Enrichment Factor (EF), and by using the ROC curve analysis. The outcome demonstrated the high predictive power of the inclusive 3D-QSAR model developed for the hERG K+ channel blockers, confirming the fundamental validity of the chosen approach for obtaining a fast proprietary cardiotoxicity predictive tool to be employed for rationally designing compounds with reduced hERG K+ channel activity at the early steps of the drug discovery trajectory.
Highlights
The hERG K+ channel is a member of the Ether-à-go-go family encoded by KCNH2 gene that consists of four identical subunits (Trudeau et al, 1995)
We have recently reported a series of predictive 3D-QSAR studies for different targets, in which a Phase common features pharmacophore has been used as the alignment rule for deriving quantitative structure-activity relationship models
A data set of 421 compounds with hERG K+ channel binding affinity spanning five orders of magnitude and belonging to different structural classes, were used for deriving a predictive hERG 3D-QSAR model
Summary
The hERG K+ channel is a member of the Ether-à-go-go family encoded by KCNH2 gene that consists of four identical subunits (Trudeau et al, 1995). To improve accuracy of investigation of large set of molecules, we have developed and validated an inclusive 3D-QSAR model aimed at obtaining a fast predictive in silico tool able to unveil potential hERG K+ channel activity of structurally diverse blockers at the early stages of our drug discovery and development process. This tool could be of pivotal importance for assisting us and others in designing active compounds for a given target endowed with limited hERG K+ channel affinity
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