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Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG

Loss of function (LOF) mutations of voltage sensitive K(+) channel proteins hERG (Kv11.1) and KCNQ1 (Kv7.1) account for the majority of instances of congenital Long QT Syndrome (cLQTS) with the dominant molecular phenotype being a mistrafficking one resulting from protein misfolding. We explored the...

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Autores principales: Zhang, Yihong, Grimwood, Amy L., Hancox, Jules C., Harmer, Stephen C., Dempsey, Christopher E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632996/
https://www.ncbi.nlm.nih.gov/pubmed/36339618
http://dx.doi.org/10.3389/fphar.2022.1010119
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author Zhang, Yihong
Grimwood, Amy L.
Hancox, Jules C.
Harmer, Stephen C.
Dempsey, Christopher E.
author_facet Zhang, Yihong
Grimwood, Amy L.
Hancox, Jules C.
Harmer, Stephen C.
Dempsey, Christopher E.
author_sort Zhang, Yihong
collection PubMed
description Loss of function (LOF) mutations of voltage sensitive K(+) channel proteins hERG (Kv11.1) and KCNQ1 (Kv7.1) account for the majority of instances of congenital Long QT Syndrome (cLQTS) with the dominant molecular phenotype being a mistrafficking one resulting from protein misfolding. We explored the use of Evolutionary Coupling (EC) analysis, which identifies evolutionarily conserved pairwise amino acid interactions that may contribute to protein structural stability, to identify regions of the channels susceptible to misfolding mutations. Comparison with published experimental trafficking data for hERG and KCNQ1 showed that the method strongly predicts “scaffolding” regions of the channel membrane domains and has useful predictive power for trafficking phenotypes of individual variants. We identified a region in and around the cytoplasmic S2-S3 loop of the hERG Voltage Sensor Domain (VSD) as susceptible to destabilising mutation, and this was confirmed using a quantitative LI-COR (®) based trafficking assay that showed severely attenuated trafficking in eight out of 10 natural hERG VSD variants selected using EC analysis. Our analysis highlights an equivalence in the scaffolding structures of the hERG and KCNQ1 membrane domains. Pathogenic variants of ion channels with an underlying mistrafficking phenotype are likely to be located within similar scaffolding structures that are identifiable by EC analysis.
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spelling pubmed-96329962022-11-04 Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG Zhang, Yihong Grimwood, Amy L. Hancox, Jules C. Harmer, Stephen C. Dempsey, Christopher E. Front Pharmacol Pharmacology Loss of function (LOF) mutations of voltage sensitive K(+) channel proteins hERG (Kv11.1) and KCNQ1 (Kv7.1) account for the majority of instances of congenital Long QT Syndrome (cLQTS) with the dominant molecular phenotype being a mistrafficking one resulting from protein misfolding. We explored the use of Evolutionary Coupling (EC) analysis, which identifies evolutionarily conserved pairwise amino acid interactions that may contribute to protein structural stability, to identify regions of the channels susceptible to misfolding mutations. Comparison with published experimental trafficking data for hERG and KCNQ1 showed that the method strongly predicts “scaffolding” regions of the channel membrane domains and has useful predictive power for trafficking phenotypes of individual variants. We identified a region in and around the cytoplasmic S2-S3 loop of the hERG Voltage Sensor Domain (VSD) as susceptible to destabilising mutation, and this was confirmed using a quantitative LI-COR (®) based trafficking assay that showed severely attenuated trafficking in eight out of 10 natural hERG VSD variants selected using EC analysis. Our analysis highlights an equivalence in the scaffolding structures of the hERG and KCNQ1 membrane domains. Pathogenic variants of ion channels with an underlying mistrafficking phenotype are likely to be located within similar scaffolding structures that are identifiable by EC analysis. Frontiers Media S.A. 2022-10-20 /pmc/articles/PMC9632996/ /pubmed/36339618 http://dx.doi.org/10.3389/fphar.2022.1010119 Text en Copyright © 2022 Zhang, Grimwood, Hancox, Harmer and Dempsey. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Zhang, Yihong
Grimwood, Amy L.
Hancox, Jules C.
Harmer, Stephen C.
Dempsey, Christopher E.
Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG
title Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG
title_full Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG
title_fullStr Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG
title_full_unstemmed Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG
title_short Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K(+) channels: Validation with hERG
title_sort evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac k(+) channels: validation with herg
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632996/
https://www.ncbi.nlm.nih.gov/pubmed/36339618
http://dx.doi.org/10.3389/fphar.2022.1010119
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