TY - JOUR
T1 - In-Silico Modeling of the Functional Role of Reduced Sialylation in Sodium and Potassium Channel Gating of Mouse Ventricular Myocytes
AU - Du, Dongping
AU - Yang, Hui
AU - Ednie, Andrew R.
AU - Bennett, Eric S.
N1 - Publisher Copyright:
© 2013 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/3
Y1 - 2018/3
N2 - 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.
AB - 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.
KW - Sodium channel
KW - cardiac action potential
KW - in-silico modeling
KW - potassium channel
KW - reduced sialylation
KW - refractory period
UR - http://www.scopus.com/inward/record.url?scp=85043226609&partnerID=8YFLogxK
U2 - 10.1109/JBHI.2017.2664579
DO - 10.1109/JBHI.2017.2664579
M3 - Article
C2 - 28182562
AN - SCOPUS:85043226609
VL - 22
SP - 631
EP - 639
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
SN - 2168-2194
IS - 2
ER -