The abuse of androstenedione, an endogenous steroid hormone, among athletes to enhance performance is a significant concern in sports. Current anti-doping detection methods are limited by short detection windows and high false-positive rates, largely due to the transient nature of primary metabolites. To address these challenges, this study employs computer-aided drug design (CADD) to identify stable, long-acting metabolites of androstenedione that can extend the detection window and improve anti-doping efficacy. The integration of CADD with sports physiology principles allows for a more comprehensive understanding of how exercise-induced metabolic fluctuations can influence the detection of these metabolites. Method: Molecular docking simulations using AutoDock (v1.5.6) were performed to analyze interactions between androstenedione, its nine metabolites, and two key enzymes involved in steroid metabolism: 17β-hydroxysteroid dehydrogenase (PDB ID: 1qyx) and cytochrome P450 17α (PDB ID: 3n9y). Ligand structures were retrieved from PubChem, optimized using Chem3D, and converted to mol2/pdbqt formats. Receptor proteins were preprocessed by removing water molecules and adding hydrogen atoms. Semi-flexible docking with 50 cycles per ligand-receptor pair was conducted, and outcomes were evaluated based on binding energy, root mean square deviation (RMSD), and hydrogen bond counts. The molecular docking results revealed that 17α-hydroxyprogesterone and 6β-hydroxyandrosterone exhibited the lowest binding energies (-8.82 and -8.81 kcal/mol, respectively) with 17β-hydroxysteroid dehydrogenase. These metabolites also had favorable RMSD values (13.35 Å and 13.27 Å) and formed two hydrogen bonds each. The stable binding conformations of these metabolites suggest that they may be retained in biological systems for longer periods, making them potential long-term biomarkers for the detection of androstenedione abuse. In contrast, interactions with cytochrome P450 17α showed weaker binding affinities, with epitestosterone displaying the lowest binding energy (-7.29 kcal/mol). The hydroxylation of 6β-hydroxyandrosterone was found to correlate with enhanced polar interactions, which may delay renal excretion. This is particularly relevant in the context of exercise physiology, where hydration status and metabolic rates can significantly influence detection thresholds. This study identifies 17α-hydroxyprogesterone and 6β-hydroxyandrosterone as promising biomarkers for detecting androstenedione abuse. These findings align with prior research on prolonged clearance rates of hydroxylated metabolites. Future research should integrate dynamic physiological models and experimental assays to refine detection thresholds. This CADD-driven approach offers a scalable framework for personalized anti-doping strategies, potentially enabling late-stage sample collection to reduce false positives caused by transient physiological fluctuations. Limitations include reliance on in silico predictions and the need for in vivo validation.
Ding et al. (Thu,) studied this question.