Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks.

ABSTRACT:

Background

Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP). Therefore recognizing drugs with TdP risk is essential. Candidate drugs that are determined not to cause cardiac ion channel blockage are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects. The objective of the present study is to develop an SAR (Structure-Activity Relationship) model that can be used as an early screen for torsadogenic (causing TdP arrhythmias) potential

SUBMITTER: Sharifi M 

PROVIDER: S-EPMC5751783 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature