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EN
Mutations in the human ether-à-go-go-related gene are linked with cardiomyocyte repolarization impairment, which, in combination with other factors, can lead to life-threatening arrhythmias. The aim of the study was to demonstrate the effect of selected mutations associated with protein trafficking problems on the action potential of the ventricular cell. To perform the simulations, the O’Hara-Rudy dynamic model was used. The modification of membrane permeability to rapid delayed rectifier current was based on data obtained from in vitro studies with the human embryonic kidney (HEK293) cell line transfected with human genes: wild type and one of the seven mutations (F805C, G601S, D456Y, I31S, R823W, F640V, and A561V). Simulations were carried out for each mutation on epicardial, endocardial, and M-cells with RR interval values of 500, 750, 1000, and 1500 ms. A positive correlation between the APD90 length and the percentage of current reduction and between APD90 and RR interval lengths was observed.
EN
Acquired long QT syndrome (LQTS) can lead to fatal ventricular arrhythmia and one of the most common reasons for developing LQTS seen in clinical settings as Torsade de Pointes (TdP) are drugs. LQTS syndrome and TdP are principally caused by the inhibition of the potassium channels encoded by hERG (the human ether-a-go-go related gene). The potassium channels and ionic currents (lkr llo, lks and others) together with calcium and sodium channels and currents (lCaL, lNa respectively) are the key elements of the electrophysiological interplay in heart. Drugs affinity to hERG channels and life-threatening interferences in heart electrophysiology resulted in withdrawal of many substances from the pharmaceutical market and some other drugs were black-boxed as potentially dangerous. Aim of the study was to develop reliable and easy to use model for the drug affinity to the hERG channel inhibition. Database used for the modeling purposes contains 447 records which were utilized during the modeling and validation levels. Dataset is freely available from the CompTox project website (www.tox-portal. net). Three various validation modes were applied to the model performance assessment to ensure highest possible reliability of the finał model: standard 10-fold cross validation procedure (10-fold CV), enhanced 10-fold cross validation (whole drugs excluded from test sets) and validation on external test set of 62 records for both previously present (different in vitro models) and absent in native dataset drugs. Pre-processing included recalculation of the original output (IC50 value - concentration of a drug which causes 50% inhibition of the ionic current) derived from the in vitro experiments, with use of the scaling factors. Random Forest algorithm with either 10 or 50 or 100 generated trees and unlimited tree depth implemented in WEKA software was used. The input consisted of 1034 parameters describing in vitro setting (3), physico-chemical properties (7), and structure (so called Chemical fingerprint -1024). Output had a binary characteristic with IC50 equal to 1 ĘM concentration as the safety threshold value (encoded as 0-safe, 1- unsafe). The performance of the best model estimated in simple 10-fold CV was 85% (1-88%, 0-82%) with an average ROC accuracy of 0.92. Implementation of rigorous 10-fold CV procedurę resulted in decrease in total accuracy to 72% (1-72%, 0-72%) with ROC value equal to 0.791. Test on the external set consists of three measures: all 62 records (total - 73%, 1-62%, 0-81%), 33 enew f records describing previously unknown drugs (total - 73%, 1-62%, 0-81%) and eold f records describing previously present drugs (total - 83%, 1-78%, 091%).
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