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In Silico Exploration of the Endocrine-Disrupting Potential of Phthalate Esters through Structural Interaction with the Human Androgen Receptor

Ariana Alarco-Cusi, Andrea Apaza-Chaña, Margot Paco-Chipana, Angela Emperatriz Centeno Lopez, Fabrizio Johnson-Corrales, K. Mena-Ulecia, M. Chávez-Fumagalli, H. Barazorda-Ccahuana

ACS Omega, 2025

Abstract

Phthalate esters are ubiquitous environmental pollutants with a well-documented potential to disrupt steroid hormone signaling, particularly through interactions with the human androgen receptor (hAR). This study used a structure-based virtual screening approach to evaluate phthalates using testosterone as the reference ligand. Three independent molecular docking platforms were used to assess binding affinity and pose consistency. The top-ranked compound underwent further investigation, including the analysis of quantum chemical descriptors, molecular dynamics (MD) simulations, binding free energy estimation, per-residue energy decomposition, and noncovalent interaction profiling. Biphenyl phthalate emerged as the leading candidate, exhibiting electrophilicity and electron-accepting capacity greater than that of testosterone, suggesting an enhanced potential for receptor engagement. MD simulations demonstrated that the biphenyl phthalate–hAR complex maintained structural stability comparable to that of testosterone-bound complex. Although MM/PBSA analysis indicated a stronger binding affinity for testosterone, primarily due to electrostatic and hydrogen-bond interactions, biphenyl phthalate binding was predominantly stabilized by van der Waals forces. These contrasting interaction patterns were further supported by energy decomposition and noncovalent interaction analyses. In conclusion, biphenyl phthalate mimics key structural and electronic features of testosterone,…

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Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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