In-Silico Modeling of the Functional Role of Reduced Sialylation in Sodium and Potassium Channel Gating of Mouse Ventricular Myocytes

Dongping Du, Hui Yang, Andrew R. Ednie, Eric S. Bennett

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Cardiac ion channels are highly glycosylated membrane proteins with up to 30% of the protein's mass containing glycans. Heart diseases often accompany individuals with congenital disorders of glycosylation (CDG). However, cardiac dysfunction among CDG patients is not yet fully understood. There is an urgent need to study how aberrant glycosylation impacts cardiac electrical signaling. Our previous works reported that congenitally reduced sialylation achieved through deletion of the sialyltransferase gene, ST3Gal4, leads to altered gating of voltage-gated Na+ and K+ channels (Nav andKv , respectively). However, linking the impact of reduced sialylation on ion channel gating to the action potential (AP) is difficult without performing computer experiments. Also, decomposing the sum of K+ currents is difficult because of complex structures and components of Kv channels (e.g., Kv4.2, and Kv1.5). In this study, we developed in-silico models to describe the functional role of reduced sialylation in both Nav and Kv gating and the AP using in vitro experimental data. Modeling results showed that reduced sialylation changesKv gating as follows: 1) The steady-state activation voltages of Kv isoforms are shifted to a more depolarized potential. 2) Aberrant K+ currents (IKslow and Ito) contribute to a prolonged AP duration, and altered Na+ current (INa) contributes to a shortened AP refractory period. This study contributes to a better understanding of the functional role of reduced sialylation in cardiac dysfunction that shows strong potential to provide new pharmaceutical targets for the treatment of CDG-related heart diseases.

Original languageEnglish (US)
Pages (from-to)631-639
Number of pages9
JournalIEEE Journal of Biomedical and Health Informatics
Volume22
Issue number2
DOIs
StatePublished - Mar 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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