In-silico modeling of glycosylation modulation dynamics in hERG ion channels and cardiac electrical signals

Dongping Du, Hui Yang, Sarah A. Norring, Eric S. Bennett

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Cardiac action potentials (AP) are produced by the orchestrated functions of ion channels. A slight change in ion channel activity may affect the AP waveform, thereby potentially increasing susceptibility to abnormal cardiac rhythms. Cardiac ion channels are heavily glycosylated, with up to 30% of a mature protein's mass comprised of glycan structures. However, little is known about how reduced glycosylation impacts the gating of hERG ( human ether-a-go-go related gene) channel, which is partially responsible for late phase 2 and phase 3 of the AP. This paper integrates the data from in vitro experiments with in-silico models to predict the glycosylation modulation dynamics in hERG ion channels and cardiac electrical signals. The gating behaviors of hERG channels expressed in Chinese Hamster Ovary (CHO) cells were measured under four glycosylation conditions, i.e., full glycosylation, reduced sialylation, mannose-rich. and N-glycanase treated. Further, we developed in-silico models to simulate glycosylation-channel interactions and predict the effects of reduced glycosylation on multiscale cardiac processes (i.e., cardiac cells, 1-D and 2-D tissues). From the in-silico models, reduced glycosylation was shown to shorten the repolarization phase of cardiac APs, thereby influencing electrical propagation in cardiac fibers and tissues. In addition, the patterns of derived electrocardiogram show that reduced glycosylation of hERG channel shortens the QT interval and decreases the re-entry rate of spiral waves. This work suggests new pharmaceutical targets for the long QT syndrome and potentially other cardiac disorders.

Original languageEnglish
Article number6510434
Pages (from-to)205-214
Number of pages10
JournalIEEE Journal of Biomedical and Health Informatics
Volume18
Issue number1
DOIs
StatePublished - Jan 2014

Keywords

  • Cardiac action potential
  • Glycosylation
  • In-silico model
  • Long-QT syndrome
  • hERG channel

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