Cargando…

A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes

Mutations are known to cause perturbations in essential functional features of integral membrane proteins, including ion channels. Even restricted or point mutations can result in substantially changed properties of ion currents. The additive effect of these alterations for a specific ion channel ca...

Descripción completa

Detalles Bibliográficos
Autores principales: Jæger, Karoline Horgmo, Edwards, Andrew G., Giles, Wayne R., Tveito, Aslak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8360568/
https://www.ncbi.nlm.nih.gov/pubmed/34383746
http://dx.doi.org/10.1371/journal.pcbi.1009233
_version_ 1783737770338942976
author Jæger, Karoline Horgmo
Edwards, Andrew G.
Giles, Wayne R.
Tveito, Aslak
author_facet Jæger, Karoline Horgmo
Edwards, Andrew G.
Giles, Wayne R.
Tveito, Aslak
author_sort Jæger, Karoline Horgmo
collection PubMed
description Mutations are known to cause perturbations in essential functional features of integral membrane proteins, including ion channels. Even restricted or point mutations can result in substantially changed properties of ion currents. The additive effect of these alterations for a specific ion channel can result in significantly changed properties of the action potential (AP). Both AP shortening and AP prolongation can result from known mutations, and the consequences can be life-threatening. Here, we present a computational method for identifying new drugs utilizing combinations of existing drugs. Based on the knowledge of theoretical effects of existing drugs on individual ion currents, our aim is to compute optimal combinations that can ‘repair’ the mutant AP waveforms so that the baseline AP-properties are restored. More specifically, we compute optimal, combined, drug concentrations such that the waveforms of the transmembrane potential and the cytosolic calcium concentration of the mutant cardiomyocytes (CMs) becomes as similar as possible to their wild type counterparts after the drug has been applied. In order to demonstrate the utility of this method, we address the question of computing an optimal drug for the short QT syndrome type 1 (SQT1). For the SQT1 mutation N588K, there are available data sets that describe the effect of various drugs on the mutated K(+) channel. These published findings are the basis for our computational analysis which can identify optimal compounds in the sense that the AP of the mutant CMs resembles essential biomarkers of the wild type CMs. Using recently developed insights regarding electrophysiological properties among myocytes from different species, we compute optimal drug combinations for hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs with the SQT1 mutation. Since the ‘composition’ of ion channels that form the AP is different for the three types of myocytes under consideration, so is the composition of the optimal drug.
format Online
Article
Text
id pubmed-8360568
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-83605682021-08-13 A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes Jæger, Karoline Horgmo Edwards, Andrew G. Giles, Wayne R. Tveito, Aslak PLoS Comput Biol Research Article Mutations are known to cause perturbations in essential functional features of integral membrane proteins, including ion channels. Even restricted or point mutations can result in substantially changed properties of ion currents. The additive effect of these alterations for a specific ion channel can result in significantly changed properties of the action potential (AP). Both AP shortening and AP prolongation can result from known mutations, and the consequences can be life-threatening. Here, we present a computational method for identifying new drugs utilizing combinations of existing drugs. Based on the knowledge of theoretical effects of existing drugs on individual ion currents, our aim is to compute optimal combinations that can ‘repair’ the mutant AP waveforms so that the baseline AP-properties are restored. More specifically, we compute optimal, combined, drug concentrations such that the waveforms of the transmembrane potential and the cytosolic calcium concentration of the mutant cardiomyocytes (CMs) becomes as similar as possible to their wild type counterparts after the drug has been applied. In order to demonstrate the utility of this method, we address the question of computing an optimal drug for the short QT syndrome type 1 (SQT1). For the SQT1 mutation N588K, there are available data sets that describe the effect of various drugs on the mutated K(+) channel. These published findings are the basis for our computational analysis which can identify optimal compounds in the sense that the AP of the mutant CMs resembles essential biomarkers of the wild type CMs. Using recently developed insights regarding electrophysiological properties among myocytes from different species, we compute optimal drug combinations for hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs with the SQT1 mutation. Since the ‘composition’ of ion channels that form the AP is different for the three types of myocytes under consideration, so is the composition of the optimal drug. Public Library of Science 2021-08-12 /pmc/articles/PMC8360568/ /pubmed/34383746 http://dx.doi.org/10.1371/journal.pcbi.1009233 Text en © 2021 Jæger et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jæger, Karoline Horgmo
Edwards, Andrew G.
Giles, Wayne R.
Tveito, Aslak
A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes
title A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes
title_full A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes
title_fullStr A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes
title_full_unstemmed A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes
title_short A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes
title_sort computational method for identifying an optimal combination of existing drugs to repair the action potentials of sqt1 ventricular myocytes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8360568/
https://www.ncbi.nlm.nih.gov/pubmed/34383746
http://dx.doi.org/10.1371/journal.pcbi.1009233
work_keys_str_mv AT jægerkarolinehorgmo acomputationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT edwardsandrewg acomputationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT gileswayner acomputationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT tveitoaslak acomputationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT jægerkarolinehorgmo computationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT edwardsandrewg computationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT gileswayner computationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes
AT tveitoaslak computationalmethodforidentifyinganoptimalcombinationofexistingdrugstorepairtheactionpotentialsofsqt1ventricularmyocytes