Advancing Torsades de pointes risk prediction: unveiling the role of drug metabolites through molecular docking

This study explores the risk of Torsades de Pointes (TdP) arrhythmia, focusing on the interactions of parent drugs and their metabolites with the Human ether-à-go-go-related gene (hERG) channel, which is crucial in cardiac electrical activity and TdP risk assessment. Using a dual-strategy molecular docking approach with AutoDock Vina and PatchDock, we analyzed clinically relevant ligand pairs: astemizole/desmethylastemizole, terfenadine/fexofenadine, and quetiapine/norquetiapine. Quantitative analysis revealed that high binding affinity does not always correlate with toxicity. For instance, the non-cardiotoxic metabolite fexofenadine exhibited a higher binding affinity (-9.3 kcal/mol) compared to its toxic parent terfenadine (-8.9 kcal/mol), but its safety is explained by physicochemical constraints (zwitterionic nature). Conversely, desmethylastemizole maintained high affinity (-9.2 kcal/mol) with a geometrically "relaxed" fit (Atomic Contact Energy: -338.36), rationalizing its sustained potency. Geometric analysis further distinguished quetiapine as a "steric blocker" (Contact Area: ~588 Å<sup>2</sup>) causing forced occlusion, whereas its metabolite norquetiapine acted as a specific ligand with a significantly smaller interface area (~417 Å<sup>2</sup>). These findings highlight the importance of focusing not only on the parent drug but also on metabolites for TdP risk assessment in new drug development. We advocate for an integrated computational framework combining binding energy, geometric complementarity, and physicochemical profiling to enhance the accuracy of early cardiac safety screenings.

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Publication Details

Journal
Toxicology Research
Published
2025-12-23
DOI
https://doi.org/10.1093/toxres/tfaf186
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Advancing Torsades de pointes risk prediction: unveiling the role of drug metabolites through molecular docking

Egemen Bilgin, Gulcin Tugcu, Ahmet Baris Aydin
Toxicology Research
Computational Drug Discovery Methods
article

Advancing Torsades de pointes risk prediction: unveiling the role of drug metabolites through molecular docking

Egemen Bilgin, Gulcin Tugcu, Ahmet Baris Aydin
article en

Abstract

This study explores the risk of Torsades de Pointes (TdP) arrhythmia, focusing on the interactions of parent drugs and their metabolites with the Human ether-à-go-go-related gene (hERG) channel, which is crucial in cardiac electrical activity and TdP risk assessment. Using a dual-strategy molecular docking approach with AutoDock Vina and PatchDock, we analyzed clinically relevant ligand pairs: astemizole/desmethylastemizole, terfenadine/fexofenadine, and quetiapine/norquetiapine. Quantitative analysis revealed that high binding affinity does not always correlate with toxicity. For instance, the non-cardiotoxic metabolite fexofenadine exhibited a higher binding affinity (-9.3 kcal/mol) compared to its toxic parent terfenadine (-8.9 kcal/mol), but its safety is explained by physicochemical constraints (zwitterionic nature). Conversely, desmethylastemizole maintained high affinity (-9.2 kcal/mol) with a geometrically "relaxed" fit (Atomic Contact Energy: -338.36), rationalizing its sustained potency. Geometric analysis further distinguished quetiapine as a "steric blocker" (Contact Area: ~588 Å<sup>2</sup>) causing forced occlusion, whereas its metabolite norquetiapine acted as a specific ligand with a significantly smaller interface area (~417 Å<sup>2</sup>). These findings highlight the importance of focusing not only on the parent drug but also on metabolites for TdP risk assessment in new drug development. We advocate for an integrated computational framework combining binding energy, geometric complementarity, and physicochemical profiling to enhance the accuracy of early cardiac safety screenings.

Toxicology ResearchVol. 15(1)
Yeditepe University (TR)
Good health and well-being
Openalex Percentile: Top 23%
Computational Drug Discovery Methods
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Advancing Torsades de pointes risk prediction: unveiling the role of drug metabolites through molecular docking — Egemen Bilgin, Gulcin Tugcu, et al. · Toxicology Research (2025) | TGRS Research Map | TGRS