Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks
作者: Mohsen SharifiDan BuzatuStephen HarrisJon Wilkes
作者单位: 1FDA’s National Center for Toxicological Research
刊名: BMC Bioinformatics, 2017, Vol.18 (14)
来源数据库: Springer Nature Journal
DOI: 10.1186/s12859-017-1895-2
关键词: Artificial Neural NetworkCardiac arrhythmiaCardiotoxicityHERGIon channelsMultilayer PerceptronQuantitative structure-activity relationshipSpectral data-activity relationshipTorsade de PointesTdP
原始语种摘要: 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are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects.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 in drug...
全文获取路径: Springer Nature  (合作)
影响因子:3.024 (2012)

  • arrhythmia 心律不齐
  • repolarization 复极化
  • cardiac 贲门
  • cardiotoxic 心脏中毒的
  • potentially 可能地
  • potassium 
  • relationship 关系
  • activity 活度
  • interatomic 原子间的
  • responsible 负责的