Prediction of Torsades de Pointes associated cardiotoxicity using computational methods

This study advocates for a comprehensive Torsades de Pointes (TdP) risk prediction, emphasizing the importance of considering both drug metabolites and parent molecules in their interactions with the hERG channel, crucial for cardiac rhythm regulation. The methodology employed includes an extensive literature review via Adverse Outcome Pathway (AOP)-helpFinder, followed by molecular docking studies using AutoDock and PatchDock to investigate the interactions between identified ligands and the hERG protein. The interactions were then visualized with BIOVIA Discovery Studio Visualizer, providing detailed insights into the complex dynamics between ligands and the hERG channel. To support these findings, ADMETlab2.0 was utilized, assessing the absorption, distribution, metabolism, excretion, and toxicity (ADMET) and physicochemical profiles of the compounds, thereby offering a deeper understanding. Findings reveal diverse effects of metabolites on TdP risk. Some metabolites, do not display hERG inhibition and thus offer a safer therapeutic alternative to parent molecules (e.g., fexofenadine compared to terfenadine). Conversely, metabolites like desmethylastemizole (versus astemizole) and paliperidone (versus risperidone) may increase TdP risk. The study highlights the significance of metabolites' unique properties and interactions with the hERG channel in determining their torsadogenic potential. The study concludes that an integrated TdP risk prediction, incorporating both parent drugs and metabolites and their interactions with the hERG channel, is crucial for enhancing drug safety and patient care, suggesting a shift towards a more holistic approach in drug development and evaluation. Key words: Torsades de Pointes, hERG Blockade, Computational Toxicology, Molecular Docking