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- W20182885 abstract "Motivation. The protein product of the human ether-a-go-go gene (hERG) is a potassium channel that when inhibited may lead to cardiac arrhythmia. At present various in vivo and in vitro models for QT prolongation and subsequent arrhythmia exist but they may not be entirely predictive for humans. Consequently a fast and reliable in silico screen for the prediction of hERG affinity values would increase the screening rate and would also lower the cost compared to experimental assay methods. Method. In this communication different approaches were employed to predict hERG K+ channel affinities. First of all different QSAR models were developed employing various molecular descriptors. Then independent software were used to predict hERG activity values: Qikprop and PASS. The software QikProp (Schrodinger, L.L.C) allows to predict pharmaceutically relevant properties for organic molecules, starting from their 3D structures and employing calculated physically significant descriptors. In addition to cell permeability, logP, solubility, blood/brain barrier permeability, the program can also predict hERG K+ channel affinity values. As an independent approach, the program PASS - Prediction of Activity Spectra for Substances - (V. Poroikov, D. Filimonov & Associates) that can predict several hundreds biological activity probability values, such as pharmacological effects, mechanisms of action, toxicity and metabolism reactions, was trained to predict the probability of hERG activity. Conclusions. The availability of different and independent methods and models able to predict hERG activity allow the application of a consensus criterion to be used as a filter in the discovery process." @default.
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- W20182885 date "2004-01-01" @default.
- W20182885 modified "2023-09-27" @default.
- W20182885 title "General and independent approaches to predict HERG affinity values" @default.
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