Several challenges for further development of a virtual heart as a platform for screening drug cardiotoxicity are discussed. Linked Articles This article is part of a themed section on Chinese Innovation in Cardiovascular Drug Discovery. of a drug on the electrical activity of the heart at multi\physical scales including cellular and tissue levels. We also conducted some simulations to demonstrate the application of the virtual heart to assess the pro\arrhythmic effects of cisapride and amiodarone. Using the model we investigated the mechanisms responsible for the differences between the two drugs on pro\arrhythmogenesis, though both prolong the QT interval of ECGs even. Several challenges for further development of a virtual heart as a platform for screening drug cardiotoxicity are discussed. Linked Articles This article is part of a themed section on Chinese Innovation in Cardiovascular Drug Discovery. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2015.172.issue-23 AbbreviationsAEallosteric effectorAPDaction potential durationAPD90APD at 90% repolarizationAPsaction potentialsBCLbasic cycle lengthCVconduction velocityCVRconduction velocity restitutionERPeffective refractory periodGRguarded receptorHHHodgkinCHuxley=?is the sodium channel current; the maximal channel conductance; the voltage\ and time\dependent activation variable; and the fast and slow inactivation variables, respectively; the cell membrane potential; and the reversal potential of the channel (for Ceftaroline fosamil acetate model details, please see Appendix A). The other is the Markov chain type of ion channel model that allows for detailed descriptions of the specific channel states and the transitions between them (Iyer that reduces the maximum conductance of the targeted ion channel. Mathematically, is expressed as: =?is the sum of the blocked Na+ channels, [and are the dissociation and association rates of different Na+ channel states respectively (for details of the model and parameters, please see Appendix A). Open in a separate window Figure 1 Schematic illustration of the theory and theory on the HH type of Na+ ion channel. Figure adapted from Comtois model proposed by Hondeghem and Katzung (1977) with transition rates from unblocked to blocked channels (model with affinity to the inactivated and activated states (Starmer and Grant, 1985). With the GR theory, Starmer and Grant (1985) proposed an HH type of Na+ channel model, with the effects of a drug shown in Figure?1B. With representing the total number of drug\blocked channels (Starmer and Grant, 1985): and are the association and dissociation rates. For details of this parameters and model, please see Appendix A. Theory of allosteric effect The allosteric effector (AE) theory differs from the state\dependent block theory in that the AE theory considers that drugs act as allosteric effectors to alter the transition dynamics of the targeted ion channels instead of simply blocking them. A recent study has implemented the AE theory, together with the MR and GR theories and Markov chain model of ion channel gating kinetics to illustrate how class I anti\arrhythmic drugs, flecainide and lidocaine, affect ventricular rhythms by inducing functional changes in the dynamics of Na+ channels (Moreno the drug/channel interactions by systematically altering the transition rates in the Fink =?=?7.8=?( ?40?mV: =?1/(0.131 +?exp[(+?10.66)/?11.1]) (A4) =?0.13???exp(?2.535??10?7+?32]} (A5) For ?40?mV: =?0.135???exp[(80 +?=?3.56???exp(0.079=?0.1212???exp(?0.01052+?40.14)]} (A9) =?0.32(+?47.13)/{1???exp[?0.1(+?47.13)]} (A10) =?0.08???exp(?=?=?m3=?=?=?= 1370.0?ms?1 ? M?1 and an unbinding rate = 1.3 10?5?ms?1 for the open state and a binding rate = 60?ms?1 ? M?1 and an unbinding rate = 2.3 10?4?ms?1 for the inactivated state. Appendix B: List of some advances in simulation of ion channelCdrug interactions Table?B1 Major models for simulating drug screening thead th rowspan=”2″ style=”border-bottom:solid 1px #000000″ colspan=”1″ Model /th th colspan=”2″ align=”center” rowspan=”1″ Using in simulating drug screening /th th rowspan=”1″ colspan=”1″ Ion channelopathy /th th rowspan=”1″ colspan=”1″ Reference /th /thead The Fitzhugh model br / (Fitzhugh, 1961) em I /em Na channel br / em I /em K channel (Starmer em et?al /em ., 1994; Starobin em et?al /em ., 1996) The BeelerCReuter model br / (Beeler and Reuter, 1977) em I /em Na channel(Starmer em et?al /em ., 1991a, 2003a, 2003b) The EbiharaCJohnson model br / (Ebihara and Johnson, 1980) em I /em Na channel(Starmer em et?al /em ., 2003a, 2003b) The LuoCRudy model br / (Luo and Rudy, 1994a, 1994b) em I /em Na channel br / em I /em K channel br / em I /em Ca channel (Clancy and Rudy, 2002; Cimponeriu em et?al /em ., 2003; Kapela em et?al /em ., 2005; Terrenoire em et?al /em ., 2005; Trenor em et?al /em ., 2005; Clancy em et?al /em ., 2007; Ahrens\Nicklas em et?al /em ., 2009; Saiz em et?al /em ., 2011) The RamirezCNattel\Courtemanche model br / (Courtemanche em et?al /em ., 1998; Ramirez em et?al /em ., 2000) em I /em Na channel br / em I /em K channel (Kneller em et?al /em ., 2005; Tsujimae em et?al /em ., 2007; Comtois em et?al /em ., 2008; Aguilar\Shardonofsky em et?al /em ., 2012; Colman em et?al /em ., 2014) The ShannonCBers model br / (Shannon em et?al /em ., 2004) em I /em Na channel(Wu em et?al /em ., 2011) The HundCRudy model br / .Then we propose a family of biomarkers that can quantitatively characterize the actions of a drug on the electrical activity of the heart at multi\physical scales including cellular and tissue levels. prolong the QT interval of ECGs. Several challenges for further development of a virtual heart as a platform for screening drug cardiotoxicity are discussed. Linked Articles This article is part of a themed section on Chinese Innovation in Cardiovascular Drug Discovery. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2015.172.issue-23 AbbreviationsAEallosteric effectorAPDaction potential durationAPD90APD at 90% repolarizationAPsaction potentialsBCLbasic cycle lengthCVconduction velocityCVRconduction velocity restitutionERPeffective refractory periodGRguarded receptorHHHodgkinCHuxley=?is the sodium channel current; the maximal channel conductance; the voltage\ and time\dependent activation variable; and the fast and slow inactivation variables, respectively; the cell membrane potential; and the reversal potential of the channel (for model details, please see Appendix A). The other is the Markov chain type of ion channel model that allows for detailed descriptions of the specific channel states and the transitions between them (Iyer that reduces the maximum conductance of the targeted ion channel. Mathematically, is expressed as: =?is the sum of the blocked Na+ channels, [and are the dissociation and association rates of different Na+ channel states respectively (for details of the model and parameters, please see Appendix A). Open in a separate window Figure 1 Schematic illustration of the theory and theory on the HH type of Na+ ion channel. Figure adapted from Comtois model proposed by Hondeghem and Katzung (1977) with transition rates from unblocked to blocked channels (model with affinity to the inactivated and activated states (Starmer and Grant, 1985). With the GR theory, Starmer and Grant (1985) proposed an HH type of Na+ channel model, with the effects of a drug shown in Figure?1B. With representing the total number of drug\blocked channels (Starmer and Grant, 1985): and are the association and dissociation rates. For details of this model and parameters, please see Appendix A. Theory of allosteric effect The allosteric effector (AE) theory differs from the state\dependent block theory in that the AE theory considers that drugs act as allosteric effectors to alter the transition dynamics of the targeted ion channels instead of simply blocking them. A recent study has implemented the AE theory, together with the MR and GR theories and Markov chain model of ion channel gating kinetics to illustrate how class I anti\arrhythmic drugs, lidocaine and flecainide, affect ventricular rhythms by inducing functional changes in the dynamics of Na+ channels (Moreno the drug/channel interactions by systematically altering the transition rates in the Fink =?=?7.8=?( ?40?mV: =?1/(0.13{1 +?exp[(+?10.66)/?11.1]}) (A4) =?0.13???exp(?2.535??10?7+?32]} (A5) For ?40?mV: =?0.135???exp[(80 +?=?3.56???exp(0.079=?0.1212???exp(?0.01052+?40.14)]} (A9) =?0.32(+?47.13)/{1???exp[?0.1(+?47.13)]} (A10) =?0.08???exp(?=?=?m3=?=?=?= 1370.0?ms?1 ? M?1 and an unbinding rate = 1.3 10?5?ms?1 for the open state and a binding rate = 60?ms?1 ? SLCO5A1 M?1 and an unbinding rate = 2.3 10?4?ms?1 for the inactivated state. Appendix B: List of some advances in simulation of ion Ceftaroline fosamil acetate channelCdrug interactions Table?B1 Major models Ceftaroline fosamil acetate for simulating drug screening thead th rowspan=”2″ style=”border-bottom:solid 1px #000000″ colspan=”1″ Model /th th colspan=”2″ align=”center” rowspan=”1″ Using in simulating drug screening /th th rowspan=”1″ colspan=”1″ Ion channelopathy /th th rowspan=”1″ colspan=”1″ Reference /th /thead The Fitzhugh model br / (Fitzhugh, 1961) em I /em Na channel br / em I /em K channel (Starmer em et?al /em ., 1994; Starobin em et?al /em ., 1996) The BeelerCReuter model br / (Beeler and Reuter, 1977) em I /em Na channel(Starmer em et?al /em ., 1991a, 2003a, 2003b) The EbiharaCJohnson model br / (Ebihara and Johnson, 1980) em I /em Na channel(Starmer em et?al /em ., 2003a, 2003b) The LuoCRudy model br / (Luo and Rudy, 1994a, 1994b) em I /em Na channel br / em I /em K channel br / em I /em Ca channel (Clancy and Rudy, 2002; Cimponeriu em et?al /em ., 2003; Kapela em et?al /em ., 2005;.