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

Abstract

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.

Fig 1. Illustration of the AP and Ca²⁺ transient biomarkers utilized in the cost function employed to identify optimal drug concentrations.

From the AP, we consider the resting membrane potential (RMP), the AP amplitude (APA), the maximal upstroke velocity (dvdt) and the AP duration at different percentages of repolarization (APD10, APD50, …, APD90). From the cytosolic Ca²⁺ transient, we consider the resting Ca²⁺ concentration (CaR), the Ca²⁺ transient amplitude (CaA), the maximal upstroke velocity (dcdt) and the calcium transient durations CaD30, CaD50, and CaD80.

Fig 2. Action potentials, Ca²⁺ transients and I_Kr currents generated using our models for wild type and SQT1 hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs.

Each panel in the upper row shows the action potentials in the wild type and SQT1 cases, and the middle row shows the Ca²⁺ transients. In the lower row, the I_Kr current from each action potential simulation is plotted as a function of the membrane potential during the entire AP waveform. Here, the filled circles mark the solution at t = 0 and the arrows indicate the direction with time. Data used in this figure can be found in S1 Data.

Fig 3. Optimal cost function values obtained by applying our computational procedure to combinations of two drugs, selected for their potential to repair the SQT1 mutation in hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs.

The numbers in the upper left to lower right diagonal report the cost function values found in searches for the optimal dose of a single drug. In addition, the pink circles indicate the lowest cost function value obtained in each case.

Fig 4. AP and Ca²⁺ transient for hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs in the wild type case (solid green), in the SQT1 case (solid red), and in the SQT1 case with the optimal combination of two drugs from Fig 3 applied (dotted yellow).

Data used in this figure can be found in S1 Data.

Fig 5. AP and Ca²⁺ transient for adult human ventricular myocytes in the wild type case, in the SQT1 case, and in the SQT1 case with the optimal dose of each of the drugs of Table 1 applied.

The selected drugs are ordered from the smallest to the highest obtained cost function values. The applied doses are specified in Table 3. Data used in this figure can be found in S1 Data.

Fig 6. Optimal cost function values obtained when our computational procedure is applied to combinations of an increasing number of drugs applied simultaneously with the goal of repairing the SQT1 mutation in hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs.

These computations were done applying the restrictions D ≤ min(EC₅₀)/2 (pink) and D ≤ min(EC₅₀) (red) for the drug doses. Data used in this figure can be found in S1 Data.

Fig 7. AP and Ca²⁺ transient waveforms for hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs in the wild type case (solid green), in the SQT1 case (solid red), and in the SQT1 case with the optimal combination of five drugs with the restriction D ≤ min(EC₅₀)/2 from Fig 6 applied (dotted yellow).

Data used in this figure can be found in S1 Data.