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...

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Main Authors: Karoline Horgmo Jæger, Andrew G Edwards, Wayne R Giles, Aslak Tveito
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-08-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1009233
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spelling doaj-6bfa1b88237b4a23a733a16602288d872021-08-17T04:32:23ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-08-01178e100923310.1371/journal.pcbi.1009233A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes.Karoline Horgmo JægerAndrew G EdwardsWayne R GilesAslak TveitoMutations 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.https://doi.org/10.1371/journal.pcbi.1009233
collection DOAJ
language English
format Article
sources DOAJ
author Karoline Horgmo Jæger
Andrew G Edwards
Wayne R Giles
Aslak Tveito
spellingShingle Karoline Horgmo Jæger
Andrew G Edwards
Wayne R Giles
Aslak Tveito
A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes.
PLoS Computational Biology
author_facet Karoline Horgmo Jæger
Andrew G Edwards
Wayne R Giles
Aslak Tveito
author_sort Karoline Horgmo Jæger
title 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_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_sort computational method for identifying an optimal combination of existing drugs to repair the action potentials of sqt1 ventricular myocytes.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2021-08-01
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.
url https://doi.org/10.1371/journal.pcbi.1009233
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