Literature DB >> 25559930

Enhanced QSAR models for drug-triggered inhibition of the main cardiac ion currents.

Barbara Wiśniowska1, Aleksander Mendyk2, Jakub Szlęk2, Michał Kołaczkowski3, Sebastian Polak1.   

Abstract

The currently changing cardiac safety testing paradigm suggests, among other things, a shift towards using in silico models of cellular electrophysiology and assessment of a concomitant block of multiple ion channels. In this study, a set of four enhanced QSAR models have been developed: for the rapid delayed rectifying potassium current (IKr), slow delayed rectifying potassium current (IKs), peak sodium current (INa) and late calcium current (ICaL), predicting ion currents changes for the specific in vitro experiment from the 2D structure of the compounds. The models are a combination of both in vitro study parameters and physico-chemical descriptors, which is a novel approach in drug-ion channels interactions modeling. Their predictive power assessed in the enhanced, more demanding than standard procedure, 10-fold cross validation was reasonably high. Rough comparison with published pure in silico hERG interaction models shows that the quality of the model predictions does not differ from other models available in the public domain, however, it takes its advantage in accounting for inter-experimental settings variability. Developed models are implemented in the Cardiac Safety Simulator, a commercially available platform enabling the in vitro-in vivo extrapolation of the drugs proarrhythmic effect and ECG simulation. A more comprehensive assessment of the effects of the compounds on ion channels allows for making more informed decisions regarding the risk - and thus avoidance - of exclusion of potentially safe and effective drugs.
Copyright © 2015 John Wiley & Sons, Ltd.

Entities:  

Keywords:  ANN; ICa; IKr; IKs; INa; QSAR model; cardiac ion channels; hERG; screening

Mesh:

Substances:

Year:  2015        PMID: 25559930     DOI: 10.1002/jat.3095

Source DB:  PubMed          Journal:  J Appl Toxicol        ISSN: 0260-437X            Impact factor:   3.446


  4 in total

1.  Drug-physiology interaction and its influence on the QT prolongation-mechanistic modeling study.

Authors:  Barbara Wiśniowska; Sebastian Polak
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-03-15       Impact factor: 2.745

2.  Effect of roll compaction on granule size distribution of microcrystalline cellulose-mannitol mixtures: computational intelligence modeling and parametric analysis.

Authors:  Pezhman Kazemi; Mohammad Hassan Khalid; Ana Pérez Gago; Peter Kleinebudde; Renata Jachowicz; Jakub Szlęk; Aleksander Mendyk
Journal:  Drug Des Devel Ther       Date:  2017-01-18       Impact factor: 4.162

3.  Quantitative systems toxicology.

Authors:  Peter Bloomingdale; Conrad Housand; Joshua F Apgar; Bjorn L Millard; Donald E Mager; John M Burke; Dhaval K Shah
Journal:  Curr Opin Toxicol       Date:  2017-08-02

4.  Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools.

Authors:  Sebastian Polak; Barbara Wiśniowska; Aleksander Mendyk; Adam Pacławski; Jakub Szlęk
Journal:  Comput Math Methods Med       Date:  2018-01-04       Impact factor: 2.238

  4 in total

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